Overview

Dataset statistics

Number of variables25
Number of observations212114
Missing cells1099585
Missing cells (%)20.7%
Duplicate rows160
Duplicate rows (%)0.1%
Total size in memory246.1 MiB
Average record size in memory1.2 KiB

Variable types

CAT19
NUM6

Warnings

Dataset has 160 (0.1%) duplicate rows Duplicates
Parent1Name has a high cardinality: 52 distinct values High cardinality
Parent1Name_es has a high cardinality: 53 distinct values High cardinality
Parent4Name has a high cardinality: 62 distinct values High cardinality
Parent4Name_es has a high cardinality: 63 distinct values High cardinality
description has a high cardinality: 108 distinct values High cardinality
description_es has a high cardinality: 102 distinct values High cardinality
code has a high cardinality: 147 distinct values High cardinality
unit has a high cardinality: 116 distinct values High cardinality
Commoditie has a high cardinality: 62 distinct values High cardinality
Commoditie_es has a high cardinality: 62 distinct values High cardinality
country is highly correlated with country_id and 1 other fieldsHigh correlation
country_id is highly correlated with country and 1 other fieldsHigh correlation
country_es is highly correlated with country_id and 1 other fieldsHigh correlation
Parent1Name_es is highly correlated with Parent1Name and 3 other fieldsHigh correlation
Parent1Name is highly correlated with Parent1Name_es and 4 other fieldsHigh correlation
Parent2Name is highly correlated with Parent1Name and 4 other fieldsHigh correlation
Parent2Name_es is highly correlated with Parent1Name and 6 other fieldsHigh correlation
Parent3Name is highly correlated with Parent1Name and 4 other fieldsHigh correlation
Parent3Name_es is highly correlated with Parent1Name and 4 other fieldsHigh correlation
Parent4Name_es is highly correlated with Parent4Name and 1 other fieldsHigh correlation
Parent4Name is highly correlated with Parent4Name_es and 1 other fieldsHigh correlation
Category is highly correlated with Parent2Name_es and 2 other fieldsHigh correlation
Commoditie_es is highly correlated with CommoditieHigh correlation
Commoditie is highly correlated with Commoditie_esHigh correlation
unitusd is highly correlated with Parent2Name and 1 other fieldsHigh correlation
Parent2Name has 137615 (64.9%) missing values Missing
Parent2Name_es has 137615 (64.9%) missing values Missing
Parent3Name has 195075 (92.0%) missing values Missing
Parent3Name_es has 195075 (92.0%) missing values Missing
Parent4Name has 201692 (95.1%) missing values Missing
Parent4Name_es has 201692 (95.1%) missing values Missing
Graph_Order has 27027 (12.7%) missing values Missing
value is highly skewed (γ1 = 61.62315453) Skewed
valueusd is highly skewed (γ1 = 87.85401746) Skewed
comm_id has 23429 (11.0%) zeros Zeros
value has 89201 (42.1%) zeros Zeros
valueusd has 89421 (42.2%) zeros Zeros

Reproduction

Analysis started2020-12-12 20:21:44.195749
Analysis finished2020-12-12 20:22:09.556072
Duration25.36 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

country_id
Categorical

HIGH CORRELATION

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
EU
27060 
US
22176 
CA
22176 
MX
20983 
CL
18360 
Other values (23)
101359 
ValueCountFrequency (%) 
EU2706012.8%
 
US2217610.5%
 
CA2217610.5%
 
MX209839.9%
 
CL183608.7%
 
CO151447.1%
 
BR116835.5%
 
CR108185.1%
 
AR98364.6%
 
GT58422.8%
 
DO54482.6%
 
JM42512.0%
 
SV39321.9%
 
EC33161.6%
 
PY29621.4%
 
NI28931.4%
 
UY28321.3%
 
PE27541.3%
 
SR27461.3%
 
HN26691.3%
 
PN25821.2%
 
TT25311.2%
 
HT20791.0%
 
BH15750.7%
 
BA15600.7%
 
Other values (3)39061.8%
 
2020-12-12T15:22:09.620628image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:09.690689image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

Overview of Unicode Properties

Unique unicode characters22
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
C6981416.5%
 
U5206812.3%
 
R350838.3%
 
A335727.9%
 
E331307.8%
 
S288546.8%
 
M252345.9%
 
O218125.1%
 
X209834.9%
 
L183604.3%
 
B175184.1%
 
T129833.1%
 
P82982.0%
 
N81441.9%
 
G70481.7%
 
Y70001.7%
 
H63231.5%
 
D54481.3%
 
J42511.0%
 
V39320.9%
 
I28930.7%
 
Z14800.3%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter424228100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C6981416.5%
 
U5206812.3%
 
R350838.3%
 
A335727.9%
 
E331307.8%
 
S288546.8%
 
M252345.9%
 
O218125.1%
 
X209834.9%
 
L183604.3%
 
B175184.1%
 
T129833.1%
 
P82982.0%
 
N81441.9%
 
G70481.7%
 
Y70001.7%
 
H63231.5%
 
D54481.3%
 
J42511.0%
 
V39320.9%
 
I28930.7%
 
Z14800.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin424228100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
C6981416.5%
 
U5206812.3%
 
R350838.3%
 
A335727.9%
 
E331307.8%
 
S288546.8%
 
M252345.9%
 
O218125.1%
 
X209834.9%
 
L183604.3%
 
B175184.1%
 
T129833.1%
 
P82982.0%
 
N81441.9%
 
G70481.7%
 
Y70001.7%
 
H63231.5%
 
D54481.3%
 
J42511.0%
 
V39320.9%
 
I28930.7%
 
Z14800.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII424228100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
C6981416.5%
 
U5206812.3%
 
R350838.3%
 
A335727.9%
 
E331307.8%
 
S288546.8%
 
M252345.9%
 
O218125.1%
 
X209834.9%
 
L183604.3%
 
B175184.1%
 
T129833.1%
 
P82982.0%
 
N81441.9%
 
G70481.7%
 
Y70001.7%
 
H63231.5%
 
D54481.3%
 
J42511.0%
 
V39320.9%
 
I28930.7%
 
Z14800.3%
 

country
Categorical

HIGH CORRELATION

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
European Union
27060 
UNITED STATES
22176 
CANADA
22176 
MEXICO
20983 
CHILE
18360 
Other values (23)
101359 
ValueCountFrequency (%) 
European Union2706012.8%
 
UNITED STATES2217610.5%
 
CANADA2217610.5%
 
MEXICO209839.9%
 
CHILE183608.7%
 
COLOMBIA151447.1%
 
BRAZIL116835.5%
 
COSTA RICA108185.1%
 
ARGENTINA98364.6%
 
GUATEMALA58422.8%
 
DOMINICAN REPUBLIC54482.6%
 
JAMAICA42512.0%
 
EL SALVADOR39321.9%
 
ECUADOR33161.6%
 
PARAGUAY29621.4%
 
NICARAGUA28931.4%
 
URUGUAY28321.3%
 
PERU27541.3%
 
SURINAME27461.3%
 
HONDURAS26691.3%
 
PANAMA25821.2%
 
TRINIDAD AND TOBAGO25311.2%
 
HAITI20791.0%
 
BAHAMAS15750.7%
 
BARBADOS15600.7%
 
Other values (3)39061.8%
 
2020-12-12T15:22:09.764752image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:09.838315image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length8
Mean length8.951455349
Min length4

Overview of Unicode Properties

Unique unicode characters31
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A25845313.6%
 
I1483747.8%
 
E1475897.8%
 
C1196556.3%
 
T1001655.3%
 
N920784.8%
 
U875684.6%
 
O852964.5%
 
n811804.3%
 
744963.9%
 
D688703.6%
 
S676523.6%
 
L670413.5%
 
R659803.5%
 
M585713.1%
 
o541202.9%
 
B422012.2%
 
G281021.5%
 
u270601.4%
 
r270601.4%
 
p270601.4%
 
e270601.4%
 
a270601.4%
 
i270601.4%
 
H246831.3%
 
Other values (6)642953.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter152657380.4%
 
Lowercase Letter29766015.7%
 
Space Separator744963.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A25845316.9%
 
I1483749.7%
 
E1475899.7%
 
C1196557.8%
 
T1001656.6%
 
N920786.0%
 
U875685.7%
 
O852965.6%
 
D688704.5%
 
S676524.4%
 
L670414.4%
 
R659804.3%
 
M585713.8%
 
B422012.8%
 
G281021.8%
 
H246831.6%
 
X209831.4%
 
P137460.9%
 
Z131630.9%
 
Y70000.5%
 
V51520.3%
 
J42510.3%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
74496100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n8118027.3%
 
o5412018.2%
 
u270609.1%
 
r270609.1%
 
p270609.1%
 
e270609.1%
 
a270609.1%
 
i270609.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin182423396.1%
 
Common744963.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A25845314.2%
 
I1483748.1%
 
E1475898.1%
 
C1196556.6%
 
T1001655.5%
 
N920785.0%
 
U875684.8%
 
O852964.7%
 
n811804.5%
 
D688703.8%
 
S676523.7%
 
L670413.7%
 
R659803.6%
 
M585713.2%
 
o541203.0%
 
B422012.3%
 
G281021.5%
 
u270601.5%
 
r270601.5%
 
p270601.5%
 
e270601.5%
 
a270601.5%
 
i270601.5%
 
H246831.4%
 
X209831.2%
 
Other values (5)433122.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
74496100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1898729100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A25845313.6%
 
I1483747.8%
 
E1475897.8%
 
C1196556.3%
 
T1001655.3%
 
N920784.8%
 
U875684.6%
 
O852964.5%
 
n811804.3%
 
744963.9%
 
D688703.6%
 
S676523.6%
 
L670413.5%
 
R659803.5%
 
M585713.1%
 
o541202.9%
 
B422012.2%
 
G281021.5%
 
u270601.4%
 
r270601.4%
 
p270601.4%
 
e270601.4%
 
a270601.4%
 
i270601.4%
 
H246831.3%
 
Other values (6)642953.4%
 

country_es
Categorical

HIGH CORRELATION

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
UNION EUROPEA
27060 
CANADÁ
22176 
ESTADOS UNIDOS
22176 
MÉXICO
20983 
CHILE
18360 
Other values (23)
101359 
ValueCountFrequency (%) 
UNION EUROPEA2706012.8%
 
CANADÁ2217610.5%
 
ESTADOS UNIDOS2217610.5%
 
MÉXICO209839.9%
 
CHILE183608.7%
 
COLOMBIA151447.1%
 
BRASIL116835.5%
 
COSTA RICA108185.1%
 
ARGENTINA98364.6%
 
GUATEMALA58422.8%
 
REPÚBLICA DOMINICANA54482.6%
 
JAMAICA42512.0%
 
EL SALVADOR39321.9%
 
ECUADOR33161.6%
 
PARAGUAY29621.4%
 
NICARAGUA28931.4%
 
URUGUAY28321.3%
 
PERÚ27541.3%
 
SURINAM27461.3%
 
HONDURAS26691.3%
 
PANAMÁ25821.2%
 
Trinidad y Tobago25311.2%
 
HAITÍ20791.0%
 
BAHAMAS15750.7%
 
BARBADOS15600.7%
 
Other values (3)39061.8%
 
2020-12-12T15:22:09.915882image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:09.991447image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length20
Median length8
Mean length8.942988204
Min length4

Overview of Unicode Properties

Unique unicode characters35
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A26405813.9%
 
O1787069.4%
 
I1682938.9%
 
N1411367.4%
 
E1287446.8%
 
C1211356.4%
 
U1064265.6%
 
S1015115.4%
 
R905094.8%
 
D834534.4%
 
744963.9%
 
L670413.5%
 
M585713.1%
 
T558132.9%
 
P408062.2%
 
B396702.1%
 
G255711.3%
 
Á247581.3%
 
H246831.3%
 
É209831.1%
 
X209831.1%
 
Ú82020.4%
 
Y70000.4%
 
V51520.3%
 
i50620.3%
 
Other values (10)341711.8%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter178953494.3%
 
Space Separator744963.9%
 
Lowercase Letter329031.7%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A26405814.8%
 
O17870610.0%
 
I1682939.4%
 
N1411367.9%
 
E1287447.2%
 
C1211356.8%
 
U1064265.9%
 
S1015115.7%
 
R905095.1%
 
D834534.7%
 
L670413.7%
 
M585713.3%
 
T558133.1%
 
P408062.3%
 
B396702.2%
 
G255711.4%
 
Á247581.4%
 
H246831.4%
 
É209831.2%
 
X209831.2%
 
Ú82020.5%
 
Y70000.4%
 
V51520.3%
 
J42510.2%
 
Í20790.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
i506215.4%
 
d506215.4%
 
a506215.4%
 
o506215.4%
 
r25317.7%
 
n25317.7%
 
y25317.7%
 
b25317.7%
 
g25317.7%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
74496100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin182243796.1%
 
Common744963.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A26405814.5%
 
O1787069.8%
 
I1682939.2%
 
N1411367.7%
 
E1287447.1%
 
C1211356.6%
 
U1064265.8%
 
S1015115.6%
 
R905095.0%
 
D834534.6%
 
L670413.7%
 
M585713.2%
 
T558133.1%
 
P408062.2%
 
B396702.2%
 
G255711.4%
 
Á247581.4%
 
H246831.4%
 
É209831.2%
 
X209831.2%
 
Ú82020.5%
 
Y70000.4%
 
V51520.3%
 
i50620.3%
 
d50620.3%
 
Other values (9)291091.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
74496100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII184091197.0%
 
None560223.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A26405814.3%
 
O1787069.7%
 
I1682939.1%
 
N1411367.7%
 
E1287447.0%
 
C1211356.6%
 
U1064265.8%
 
S1015115.5%
 
R905094.9%
 
D834534.5%
 
744964.0%
 
L670413.6%
 
M585713.2%
 
T558133.0%
 
P408062.2%
 
B396702.2%
 
G255711.4%
 
H246831.3%
 
X209831.1%
 
Y70000.4%
 
V51520.3%
 
i50620.3%
 
d50620.3%
 
a50620.3%
 
o50620.3%
 
Other values (6)169060.9%
 

Most frequent None characters

ValueCountFrequency (%) 
Á2475844.2%
 
É2098337.5%
 
Ú820214.6%
 
Í20793.7%
 

Parent1Name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct52
Distinct (%)< 0.1%
Missing592
Missing (%)0.3%
Memory size1.6 MiB
Producer Single Commodity Transfers
25532 
Budgetary Transfers
20990 
Producer Support Estimate (PSE)
16328 
Payments based on input use
14724 
Value of Production (at farm gate)
 
10906
Other values (47)
123042 
ValueCountFrequency (%) 
Producer Single Commodity Transfers2553212.0%
 
Budgetary Transfers209909.9%
 
Producer Support Estimate (PSE)163287.7%
 
Payments based on input use147246.9%
 
Value of Production (at farm gate)109065.1%
 
Level of Production100734.7%
 
Payments based on output95164.5%
 
General Services Support Estimate (GSSE)68543.2%
 
Market Transfers61252.9%
 
Market Price Support (MPS)55052.6%
 
Producer NPC54662.6%
 
% Producer Single Commodity Transfers54522.6%
 
Consumer NPC53822.5%
 
Producer Price (at farm gate)51972.5%
 
Market Price Differential51952.4%
 
Level of Consumption51952.4%
 
Transfers to Producers From Consumers51952.4%
 
Reference Price (at farm gate)51952.4%
 
Value of Consumption (at farm gate)51952.4%
 
Other Transfers From Consumers51942.4%
 
Excess Feed Cost51302.4%
 
Consumer Single Commodity Transfers (CSCT)51112.4%
 
Consumption Price (at farm gate)50982.4%
 
Payments based on output per tonne45932.2%
 
Price levies based on output(-)37811.8%
 
Other values (27)85904.0%
 
2020-12-12T15:22:10.075520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.160593image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length63
Median length30
Mean length27.82870532
Min length3

Overview of Unicode Properties

Unique unicode characters46
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
63741910.8%
 
e5550229.4%
 
r5063898.6%
 
o3866326.5%
 
t3729896.3%
 
a3381925.7%
 
s3379095.7%
 
n2980705.0%
 
u2636554.5%
 
m2121243.6%
 
i2049263.5%
 
d1825633.1%
 
P1807183.1%
 
f1604452.7%
 
c1385612.3%
 
S1169242.0%
 
p1155622.0%
 
C1022931.7%
 
g929521.6%
 
l894361.5%
 
y874691.5%
 
T847791.4%
 
(719001.2%
 
)719001.2%
 
E554860.9%
 
Other values (21)2385434.0%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter443226275.1%
 
Uppercase Letter67882511.5%
 
Space Separator63741910.8%
 
Open Punctuation719001.2%
 
Close Punctuation719001.2%
 
Other Punctuation61330.1%
 
Dash Punctuation44190.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P18071826.6%
 
S11692417.2%
 
C10229315.1%
 
T8477912.5%
 
E554868.2%
 
M229223.4%
 
B213263.1%
 
V176972.6%
 
F161112.4%
 
L153792.3%
 
G138492.0%
 
N118771.7%
 
R64981.0%
 
O58370.9%
 
D52100.8%
 
A19040.3%
 
U15< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e55502212.5%
 
r50638911.4%
 
o3866328.7%
 
t3729898.4%
 
a3381927.6%
 
s3379097.6%
 
n2980706.7%
 
u2636555.9%
 
m2121244.8%
 
i2049264.6%
 
d1825634.1%
 
f1604453.6%
 
c1385613.1%
 
p1155622.6%
 
g929522.1%
 
l894362.0%
 
y874692.0%
 
b331470.7%
 
v262850.6%
 
k168250.4%
 
h66890.2%
 
x58280.1%
 
w592< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
637419100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(71900100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)71900100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
%545288.9%
 
,68111.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-4419100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin511108786.6%
 
Common79177113.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e55502210.9%
 
r5063899.9%
 
o3866327.6%
 
t3729897.3%
 
a3381926.6%
 
s3379096.6%
 
n2980705.8%
 
u2636555.2%
 
m2121244.2%
 
i2049264.0%
 
d1825633.6%
 
P1807183.5%
 
f1604453.1%
 
c1385612.7%
 
S1169242.3%
 
p1155622.3%
 
C1022932.0%
 
g929521.8%
 
l894361.7%
 
y874691.7%
 
T847791.7%
 
E554861.1%
 
b331470.6%
 
v262850.5%
 
M229220.4%
 
Other values (15)1456372.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
63741980.5%
 
(719009.1%
 
)719009.1%
 
%54520.7%
 
-44190.6%
 
,6810.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5902858100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
63741910.8%
 
e5550229.4%
 
r5063898.6%
 
o3866326.5%
 
t3729896.3%
 
a3381925.7%
 
s3379095.7%
 
n2980705.0%
 
u2636554.5%
 
m2121243.6%
 
i2049263.5%
 
d1825633.1%
 
P1807183.1%
 
f1604452.7%
 
c1385612.3%
 
S1169242.0%
 
p1155622.0%
 
C1022931.7%
 
g929521.6%
 
l894361.5%
 
y874691.5%
 
T847791.4%
 
(719001.2%
 
)719001.2%
 
E554860.9%
 
Other values (21)2385434.0%
 

Parent1Name_es
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct53
Distinct (%)< 0.1%
Missing932
Missing (%)0.4%
Memory size1.6 MiB
Transferencias al Productor de un Producto Individual
25532 
Transferencias Presupuestarias
20990 
Estimado de Apoyo al Productor
16021 
Pagos basados en el uso de Insumos
13502 
Valor de Producción (en finca)
 
10906
Other values (48)
124231 
ValueCountFrequency (%) 
Transferencias al Productor de un Producto Individual2553212.0%
 
Transferencias Presupuestarias209909.9%
 
Estimado de Apoyo al Productor160217.6%
 
Pagos basados en el uso de Insumos135026.4%
 
Valor de Producción (en finca)109065.1%
 
Nivel de Producción100734.7%
 
Pagos Basados en la Producción95164.5%
 
Estimado de Apoyo a Servicios Generales (EASG)68543.2%
 
Transferencias de Mercado61252.9%
 
Apoyo al Precio de Mercado55052.6%
 
CPN del Productor54662.6%
 
Transferencias al Productor de un Producto Individual (%)54522.6%
 
Precio al Productor (Precio en finca)51972.5%
 
Nivel de Consumo51952.4%
 
Diferencial de Precio de Mercado51952.4%
 
Precio de Referencia (Precio en finca)51952.4%
 
Transferencias a los Productores de los Consumidores51952.4%
 
Valor de Consumo (Precio en finca)51952.4%
 
Otras Transferencias de los Consumidores51942.4%
 
Exceso de Coste del Pienso51302.4%
 
Pagos Basados en la Producción por Tonelada51262.4%
 
Transferencias al Consumidor de un Producto Individual51112.4%
 
CPN del Consumidor51112.4%
 
Precio de Consumo (Precio en finca)50982.4%
 
Gravámenes de precio basados en la producción (-)37811.8%
 
Other values (28)95174.5%
 
2020-12-12T15:22:10.246166image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.326736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length86
Median length32
Mean length35.18091215
Min length3

Overview of Unicode Properties

Unique unicode characters48
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
89437412.0%
 
e6444968.6%
 
o6408698.6%
 
a5581947.5%
 
r5525557.4%
 
s4985646.7%
 
d4943716.6%
 
n4553836.1%
 
i3947365.3%
 
c3892895.2%
 
u3272574.4%
 
P2544113.4%
 
l2246933.0%
 
t1619692.2%
 
f1197901.6%
 
T843471.1%
 
m821231.1%
 
p659270.9%
 
v620440.8%
 
C553990.7%
 
I512440.7%
 
(504080.7%
 
)504080.7%
 
A413080.6%
 
ó411290.6%
 
Other values (23)2670763.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter580461777.8%
 
Space Separator89437412.0%
 
Uppercase Letter6518548.7%
 
Open Punctuation504080.7%
 
Close Punctuation504080.7%
 
Other Punctuation63150.1%
 
Dash Punctuation41170.1%
 
Decimal Number271< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P25441139.0%
 
T8434712.9%
 
C553998.5%
 
I512447.9%
 
A413086.3%
 
E388366.0%
 
N268564.1%
 
V179682.8%
 
G175412.7%
 
M174172.7%
 
B159532.4%
 
S141742.2%
 
R56850.9%
 
O54900.8%
 
D52100.8%
 
U15< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e64449611.1%
 
o64086911.0%
 
a5581949.6%
 
r5525559.5%
 
s4985648.6%
 
d4943718.5%
 
n4553837.8%
 
i3947366.8%
 
c3892896.7%
 
u3272575.6%
 
l2246933.9%
 
t1619692.8%
 
f1197902.1%
 
m821231.4%
 
p659271.1%
 
v620441.1%
 
ó411290.7%
 
g307500.5%
 
y298610.5%
 
b187730.3%
 
x51300.1%
 
á37810.1%
 
j1885< 0.1%
 
í1048< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
894374100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(50408100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)50408100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
%545286.3%
 
,5929.4%
 
.2714.3%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-4117100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
3271100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin645647186.5%
 
Common100589313.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e64449610.0%
 
o6408699.9%
 
a5581948.6%
 
r5525558.6%
 
s4985647.7%
 
d4943717.7%
 
n4553837.1%
 
i3947366.1%
 
c3892896.0%
 
u3272575.1%
 
P2544113.9%
 
l2246933.5%
 
t1619692.5%
 
f1197901.9%
 
T843471.3%
 
m821231.3%
 
p659271.0%
 
v620441.0%
 
C553990.9%
 
I512440.8%
 
A413080.6%
 
ó411290.6%
 
E388360.6%
 
g307500.5%
 
y298610.5%
 
Other values (15)1569262.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
89437488.9%
 
(504085.0%
 
)504085.0%
 
%54520.5%
 
-41170.4%
 
,5920.1%
 
.271< 0.1%
 
3271< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII741640699.4%
 
None459580.6%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
89437412.1%
 
e6444968.7%
 
o6408698.6%
 
a5581947.5%
 
r5525557.5%
 
s4985646.7%
 
d4943716.7%
 
n4553836.1%
 
i3947365.3%
 
c3892895.2%
 
u3272574.4%
 
P2544113.4%
 
l2246933.0%
 
t1619692.2%
 
f1197901.6%
 
T843471.1%
 
m821231.1%
 
p659270.9%
 
v620440.8%
 
C553990.7%
 
I512440.7%
 
(504080.7%
 
)504080.7%
 
A413080.6%
 
E388360.5%
 
Other values (20)2234113.0%
 

Most frequent None characters

ValueCountFrequency (%) 
ó4112989.5%
 
á37818.2%
 
í10482.3%
 

Parent2Name
Categorical

HIGH CORRELATION
MISSING

Distinct30
Distinct (%)< 0.1%
Missing137615
Missing (%)64.9%
Memory size1.6 MiB
Support based on commodity outputs
16804 
Payments based on input use
6786 
Transfers to Producers From Taxpayers
5248 
Variable input use
5073 
Payments based on non-current A/AN/R/I, production required
4999 
Other values (25)
35589 
ValueCountFrequency (%) 
Support based on commodity outputs168047.9%
 
Payments based on input use67863.2%
 
Transfers to Producers From Taxpayers52482.5%
 
Variable input use50732.4%
 
Payments based on non-current A/AN/R/I, production required49992.4%
 
Fixed capital formation48402.3%
 
On-farm services48112.3%
 
Payments based on current A/AN/R/I, production required, single commodity48032.3%
 
Price levies (-)46352.2%
 
Transfers to consumers from taxpayers45482.1%
 
J. Development and maintenance of infrastructure17830.8%
 
Payments based on non-commodity criteria14660.7%
 
I. Inspection and control14200.7%
 
H. Agricultural knowledge and innovation system11540.5%
 
K. Marketing and promotion10410.5%
 
Price Levies (-)5500.3%
 
Transfers to Consumers From Taxpayers5210.2%
 
Total Value of Production of Which, Share of MPS Commodities (%)3990.2%
 
Value of Consumption (farm gate): MPS Commodities3990.2%
 
Payments based on non-current A/AN/R/I, production not required3830.2%
 
Payments based on current A/AN/R/I, production required3810.2%
 
M. Miscellaneous3760.2%
 
L. Cost of public stockholding3550.2%
 
Transfers to Producers From Consumers (-)3470.2%
 
Other Transfers From Consumers (-)3470.2%
 
Other values (5)10300.5%
 
(Missing)13761564.9%
 
2020-12-12T15:22:10.411809image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.491878image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length73
Median length3
Mean length14.03664067
Min length3

Overview of Unicode Properties

Unique unicode characters52
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n43658314.7%
 
2855509.6%
 
a2726099.2%
 
o2097847.0%
 
e1952466.6%
 
t1726445.8%
 
r1712005.8%
 
s1640055.5%
 
u1260904.2%
 
i1139813.8%
 
m1008293.4%
 
d990193.3%
 
p936263.1%
 
c817162.7%
 
y540551.8%
 
b410501.4%
 
f317181.1%
 
/316981.1%
 
P308441.0%
 
l294791.0%
 
A222960.7%
 
S180110.6%
 
-175380.6%
 
T171790.6%
 
,157680.5%
 
Other values (27)1448504.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter244717682.2%
 
Space Separator2855509.6%
 
Uppercase Letter1593475.4%
 
Other Punctuation544031.8%
 
Dash Punctuation175380.6%
 
Open Punctuation66770.2%
 
Close Punctuation66770.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n43658317.8%
 
a27260911.1%
 
o2097848.6%
 
e1952468.0%
 
t1726447.1%
 
r1712007.0%
 
s1640056.7%
 
u1260905.2%
 
i1139814.7%
 
m1008294.1%
 
d990194.0%
 
p936263.8%
 
c817163.3%
 
y540552.2%
 
b410501.7%
 
f317181.3%
 
l294791.2%
 
x154940.6%
 
v129430.5%
 
q105660.4%
 
g89260.4%
 
k25500.1%
 
h18990.1%
 
w1164< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P3084419.4%
 
A2229614.0%
 
S1801111.3%
 
T1717910.8%
 
I134168.4%
 
F116407.3%
 
N105666.6%
 
R105666.6%
 
V58713.7%
 
O51583.2%
 
C34002.1%
 
M29781.9%
 
J17831.1%
 
D17831.1%
 
H11640.7%
 
K10510.7%
 
L9050.6%
 
W3990.3%
 
E3370.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
285550100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(6677100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)6677100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/3169858.3%
 
,1576829.0%
 
.613911.3%
 
:3990.7%
 
%3990.7%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-17538100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin260652387.5%
 
Common37084512.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n43658316.7%
 
a27260910.5%
 
o2097848.0%
 
e1952467.5%
 
t1726446.6%
 
r1712006.6%
 
s1640056.3%
 
u1260904.8%
 
i1139814.4%
 
m1008293.9%
 
d990193.8%
 
p936263.6%
 
c817163.1%
 
y540552.1%
 
b410501.6%
 
f317181.2%
 
P308441.2%
 
l294791.1%
 
A222960.9%
 
S180110.7%
 
T171790.7%
 
x154940.6%
 
I134160.5%
 
v129430.5%
 
F116400.4%
 
Other values (18)710662.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
28555077.0%
 
/316988.5%
 
-175384.7%
 
,157684.3%
 
(66771.8%
 
)66771.8%
 
.61391.7%
 
:3990.1%
 
%3990.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2977368100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n43658314.7%
 
2855509.6%
 
a2726099.2%
 
o2097847.0%
 
e1952466.6%
 
t1726445.8%
 
r1712005.8%
 
s1640055.5%
 
u1260904.2%
 
i1139813.8%
 
m1008293.4%
 
d990193.3%
 
p936263.1%
 
c817162.7%
 
y540551.8%
 
b410501.4%
 
f317181.1%
 
/316981.1%
 
P308441.0%
 
l294791.0%
 
A222960.7%
 
S180110.6%
 
-175380.6%
 
T171790.6%
 
,157680.5%
 
Other values (27)1448504.9%
 

Parent2Name_es
Categorical

HIGH CORRELATION
MISSING

Distinct34
Distinct (%)< 0.1%
Missing137615
Missing (%)64.9%
Memory size1.6 MiB
Apoyo Basado en Producción de Productos
11345 
Apoyo Basados en la Producción de Productos
5459 
Transferencias a los Productores de los Contribuyentes
5248 
Uso de Insumos Variables
5073 
Transferencias a los Consumidores de los Contribuyentes
5069 
Other values (29)
42305 
ValueCountFrequency (%) 
Apoyo Basado en Producción de Productos113455.3%
 
Apoyo Basados en la Producción de Productos54592.6%
 
Transferencias a los Productores de los Contribuyentes52482.5%
 
Uso de Insumos Variables50732.4%
 
Transferencias a los Consumidores de los Contribuyentes50692.4%
 
Formación de Capital Fijo48402.3%
 
Servicios en finca48112.3%
 
Pagos Basados en S/NA/V/I Actuales, Producción Requerida, Producto Individual48032.3%
 
Pagos Basados en S/NA/V/I No-Actuales, Producción Requerida47602.2%
 
Gravámenes de Precio (-)46352.2%
 
Pagos basados en el uso de Insumos46202.2%
 
J. Desarrollo y Mantenimiento de Infraestructura17830.8%
 
Pagos Basados en Uso de Insumos15890.7%
 
Pagos Basados en Criterios No Relacionados con el Producto14660.7%
 
I. Inspección y Control14200.7%
 
H. Conocimiento Agropecuario y Sistema de Innovación10770.5%
 
K. Comercialización y Promoción10410.5%
 
Pagos Basados en el uso de Insumos5770.3%
 
Gravámenes de Precio5500.3%
 
Valor Total de la Producción, de la cual, Proporción de Productos APM3990.2%
 
Valor del Consumo (Precios en finca): Productos APM3990.2%
 
Pagos Misceláneos3870.2%
 
Pagos Basados en S/NA/V/I Actuales, Producción Requerida3810.2%
 
M. Misceláneos3760.2%
 
Transferencias a los productores de los consumidores (-)3470.2%
 
Other values (9)20441.0%
 
(Missing)13761564.9%
 
2020-12-12T15:22:10.572447image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.651015image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length77
Median length3
Mean length16.36138114
Min length3

Overview of Unicode Properties

Unique unicode characters54
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n45054313.0%
 
36953910.6%
 
a34853010.0%
 
o3010148.7%
 
s2442037.0%
 
e2350196.8%
 
d1767545.1%
 
r1577954.5%
 
c1459784.2%
 
i1378434.0%
 
u1224593.5%
 
P842702.4%
 
t806252.3%
 
l718082.1%
 
A402531.2%
 
ó379241.1%
 
m355821.0%
 
I330151.0%
 
y325290.9%
 
/316980.9%
 
B310020.9%
 
C264080.8%
 
p255660.7%
 
g207060.6%
 
b203650.6%
 
Other values (29)2090506.0%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter270281577.9%
 
Space Separator36953910.6%
 
Uppercase Letter3211719.3%
 
Other Punctuation544031.6%
 
Dash Punctuation110940.3%
 
Open Punctuation57280.2%
 
Close Punctuation57280.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n45054316.7%
 
a34853012.9%
 
o30101411.1%
 
s2442039.0%
 
e2350198.7%
 
d1767546.5%
 
r1577955.8%
 
c1459785.4%
 
i1378435.1%
 
u1224594.5%
 
t806253.0%
 
l718082.7%
 
ó379241.4%
 
m355821.3%
 
y325291.2%
 
p255660.9%
 
g207060.8%
 
b203650.8%
 
f185960.7%
 
v159630.6%
 
q105660.4%
 
á59480.2%
 
j48400.2%
 
z1041< 0.1%
 
ú322< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P8427026.2%
 
A4025312.5%
 
I3301510.3%
 
B310029.7%
 
C264088.2%
 
N177975.5%
 
S165415.2%
 
V164375.1%
 
R120323.7%
 
T113593.5%
 
F96803.0%
 
U66622.1%
 
G51851.6%
 
M37201.2%
 
J17830.6%
 
D17830.6%
 
H11640.4%
 
K10410.3%
 
O6840.2%
 
L3550.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
369539100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(5728100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)5728100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/3169858.3%
 
,1616729.7%
 
.613911.3%
 
:3990.7%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-11094100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin302398687.1%
 
Common44649212.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n45054314.9%
 
a34853011.5%
 
o30101410.0%
 
s2442038.1%
 
e2350197.8%
 
d1767545.8%
 
r1577955.2%
 
c1459784.8%
 
i1378434.6%
 
u1224594.0%
 
P842702.8%
 
t806252.7%
 
l718082.4%
 
A402531.3%
 
ó379241.3%
 
m355821.2%
 
I330151.1%
 
y325291.1%
 
B310021.0%
 
C264080.9%
 
p255660.8%
 
g207060.7%
 
b203650.7%
 
f185960.6%
 
N177970.6%
 
Other values (21)1274024.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
36953982.8%
 
/316987.1%
 
,161673.6%
 
-110942.5%
 
.61391.4%
 
(57281.3%
 
)57281.3%
 
:3990.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII342598898.7%
 
None444901.3%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n45054313.2%
 
36953910.8%
 
a34853010.2%
 
o3010148.8%
 
s2442037.1%
 
e2350196.9%
 
d1767545.2%
 
r1577954.6%
 
c1459784.3%
 
i1378434.0%
 
u1224593.6%
 
P842702.5%
 
t806252.4%
 
l718082.1%
 
A402531.2%
 
m355821.0%
 
I330151.0%
 
y325290.9%
 
/316980.9%
 
B310020.9%
 
C264080.8%
 
p255660.7%
 
g207060.6%
 
b203650.6%
 
f185960.5%
 
Other values (25)1838885.4%
 

Most frequent None characters

ValueCountFrequency (%) 
ó3792485.2%
 
á594813.4%
 
ú3220.7%
 
í2960.7%
 

Parent3Name
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)0.2%
Missing195075
Missing (%)92.0%
Memory size1.6 MiB
Market Price Support
10854 
On-farm services
 
398
Fixed capital formation
 
398
Variable input use
 
394
H1. Agricultural knowledge generation
 
341
Other values (28)
4654 
ValueCountFrequency (%) 
Market Price Support108545.1%
 
On-farm services3980.2%
 
Fixed capital formation3980.2%
 
Variable input use3940.2%
 
H1. Agricultural knowledge generation3410.2%
 
H2. Agricultural knowledge transfer3410.2%
 
J2. Storage, marketing and other physical infrastructure3370.2%
 
J3. Institutional infrastructure3320.2%
 
J1. Hydrological infrastructure3300.2%
 
I1. Agricultural product safety and inspection3290.2%
 
I2. Pest and disease inspection and control3220.2%
 
long-term resource retirement3170.1%
 
other non-commodity criteria3120.1%
 
a specific non-commodity output3120.1%
 
J4. Farm restructuring3060.1%
 
I3. Input control2990.1%
 
K1. Collective schemes for processing and marketing2970.1%
 
K2. Promotion of agricultural products2960.1%
 
Payments based on output92< 0.1%
 
LonG-Term Resource Retirement47< 0.1%
 
Other NoN-Commodity Criteria45< 0.1%
 
a Specific NoN-Commodity Output45< 0.1%
 
H2. Agricultural Knowledge Transfer44< 0.1%
 
H1. Agricultural Knowledge Generation43< 0.1%
 
I1. Agricultural Product Safety and Inspection27< 0.1%
 
Other values (8)1810.1%
 
(Missing)19507592.0%
 
2020-12-12T15:22:10.736088image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.810652image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length56
Median length3
Mean length4.720947226
Min length3

Overview of Unicode Properties

Unique unicode characters49
Unique unicode categories6 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40297040.2%
 
a21765021.7%
 
r495304.9%
 
407324.1%
 
t374783.7%
 
e363293.6%
 
p255882.6%
 
i236662.4%
 
o232232.3%
 
c201892.0%
 
u199212.0%
 
k122171.2%
 
P117191.2%
 
S113101.1%
 
M109011.1%
 
s82030.8%
 
l75120.8%
 
d50660.5%
 
g49140.5%
 
m46450.5%
 
.38250.4%
 
f36070.4%
 
y18760.2%
 
I18140.2%
 
-14760.1%
 
Other values (24)150181.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter90835490.7%
 
Uppercase Letter428104.3%
 
Space Separator407324.1%
 
Other Punctuation41820.4%
 
Decimal Number38250.4%
 
Dash Punctuation14760.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40297044.4%
 
a21765024.0%
 
r495305.5%
 
t374784.1%
 
e363294.0%
 
p255882.8%
 
i236662.6%
 
o232232.6%
 
c201892.2%
 
u199212.2%
 
k122171.3%
 
s82030.9%
 
l75120.8%
 
d50660.6%
 
g49140.5%
 
m46450.5%
 
f36070.4%
 
y18760.2%
 
h13950.2%
 
w7690.1%
 
v7220.1%
 
b4860.1%
 
x398< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P1171927.4%
 
S1131026.4%
 
M1090125.5%
 
I18144.2%
 
J13863.2%
 
A11522.7%
 
H11262.6%
 
K7341.7%
 
F7181.7%
 
O5081.2%
 
C5051.2%
 
V3940.9%
 
N1800.4%
 
R1080.3%
 
T910.2%
 
G900.2%
 
L470.1%
 
D270.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
40732100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1476100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1142137.2%
 
2141437.0%
 
367017.5%
 
43208.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.382591.5%
 
,3578.5%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin95116495.0%
 
Common502155.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40297042.4%
 
a21765022.9%
 
r495305.2%
 
t374783.9%
 
e363293.8%
 
p255882.7%
 
i236662.5%
 
o232232.4%
 
c201892.1%
 
u199212.1%
 
k122171.3%
 
P117191.2%
 
S113101.2%
 
M109011.1%
 
s82030.9%
 
l75120.8%
 
d50660.5%
 
g49140.5%
 
m46450.5%
 
f36070.4%
 
y18760.2%
 
I18140.2%
 
h13950.1%
 
J13860.1%
 
A11520.1%
 
Other values (16)69030.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
4073281.1%
 
.38257.6%
 
-14762.9%
 
114212.8%
 
214142.8%
 
36701.3%
 
,3570.7%
 
43200.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1001379100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40297040.2%
 
a21765021.7%
 
r495304.9%
 
407324.1%
 
t374783.7%
 
e363293.6%
 
p255882.6%
 
i236662.4%
 
o232232.3%
 
c201892.0%
 
u199212.0%
 
k122171.2%
 
P117191.2%
 
S113101.1%
 
M109011.1%
 
s82030.8%
 
l75120.8%
 
d50660.5%
 
g49140.5%
 
m46450.5%
 
.38250.4%
 
f36070.4%
 
y18760.2%
 
I18140.2%
 
-14760.1%
 
Other values (24)150181.5%
 

Parent3Name_es
Categorical

HIGH CORRELATION
MISSING

Distinct22
Distinct (%)0.1%
Missing195075
Missing (%)92.0%
Memory size1.6 MiB
Apoyo al Precio de Mercado
10854 
Formación de Capital Fijo
 
398
Servicios en finca
 
398
Uso de Insumos Variables
 
394
H2. Transferencia de Conocimiento Agropecuario
 
385
Other values (17)
4610 
ValueCountFrequency (%) 
Apoyo al Precio de Mercado108545.1%
 
Formación de Capital Fijo3980.2%
 
Servicios en finca3980.2%
 
Uso de Insumos Variables3940.2%
 
H2. Transferencia de Conocimiento Agropecuario3850.2%
 
H1. Generación de Conocimiento Agropecuario3840.2%
 
Retiro de Recursos a Largo Plazo3640.2%
 
Otros Criterios No Relacionados con el Producto3570.2%
 
Producción Especifica No Relacionada con el Producto3570.2%
 
J2. Almacenamiento, Mercadeo y Otras Infraestructuras Físicas3570.2%
 
I1. Inocuidad de Productos Agropecuario e Inspección3560.2%
 
J3. Infraestructura Institucional3520.2%
 
I2. Inspección y Control de Plagas y Enfermedades3490.2%
 
J1. Infraestructura Hidrológica3300.2%
 
K2. Promoción de Productos Agropecuarios3230.2%
 
J4. Restructuración de Fincas3200.2%
 
I3. Control de Insumos3000.1%
 
K1. Esquemas Colectivos para Procesamiento y Mercadeo2970.1%
 
Pagos Basados en la Producción92< 0.1%
 
K1. Esquemas Colectivos Para Procesamiento y Mercadeo27< 0.1%
 
J1. Infraestructura hidrológica27< 0.1%
 
I3. Contro de Insumos18< 0.1%
 
(Missing)19507592.0%
 
2020-12-12T15:22:10.886718image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:10.962283image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length61
Median length3
Mean length5.206610596
Min length3

Overview of Unicode Properties

Unique unicode characters52
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40365436.5%
 
a23365621.2%
 
694256.3%
 
o643865.8%
 
e509264.6%
 
r381733.5%
 
c375523.4%
 
d303952.8%
 
i251502.3%
 
l159181.4%
 
P141751.3%
 
p140591.3%
 
A126591.1%
 
s126141.1%
 
y122331.1%
 
M115351.0%
 
t91430.8%
 
u81700.7%
 
I42140.4%
 
m39130.4%
 
.38250.3%
 
ó29360.3%
 
g26100.2%
 
f25550.2%
 
C25150.2%
 
Other values (27)180041.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter97062987.9%
 
Space Separator694256.3%
 
Uppercase Letter563345.1%
 
Other Punctuation41820.4%
 
Decimal Number38250.3%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40365441.6%
 
a23365624.1%
 
o643866.6%
 
e509265.2%
 
r381733.9%
 
c375523.9%
 
d303953.1%
 
i251502.6%
 
l159181.6%
 
p140591.4%
 
s126141.3%
 
y122331.3%
 
t91430.9%
 
u81700.8%
 
m39130.4%
 
ó29360.3%
 
g26100.3%
 
f25550.3%
 
v7220.1%
 
j398< 0.1%
 
b394< 0.1%
 
z364< 0.1%
 
í357< 0.1%
 
q324< 0.1%
 
h27< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P1417525.2%
 
A1265922.5%
 
M1153520.5%
 
I42147.5%
 
C25154.5%
 
R17623.1%
 
F14732.6%
 
J13862.5%
 
H10992.0%
 
E10301.8%
 
O7141.3%
 
N7141.3%
 
K6471.1%
 
S3980.7%
 
U3940.7%
 
V3940.7%
 
T3850.7%
 
G3840.7%
 
L3640.6%
 
B920.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
69425100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1142137.2%
 
2141437.0%
 
367017.5%
 
43208.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.382591.5%
 
,3578.5%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin102696393.0%
 
Common774327.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40365439.3%
 
a23365622.8%
 
o643866.3%
 
e509265.0%
 
r381733.7%
 
c375523.7%
 
d303953.0%
 
i251502.4%
 
l159181.6%
 
P141751.4%
 
p140591.4%
 
A126591.2%
 
s126141.2%
 
y122331.2%
 
M115351.1%
 
t91430.9%
 
u81700.8%
 
I42140.4%
 
m39130.4%
 
ó29360.3%
 
g26100.3%
 
f25550.2%
 
C25150.2%
 
R17620.2%
 
F14730.1%
 
Other values (20)105871.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
6942589.7%
 
.38254.9%
 
114211.8%
 
214141.8%
 
36700.9%
 
,3570.5%
 
43200.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII110110299.7%
 
None32930.3%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40365436.7%
 
a23365621.2%
 
694256.3%
 
o643865.8%
 
e509264.6%
 
r381733.5%
 
c375523.4%
 
d303952.8%
 
i251502.3%
 
l159181.4%
 
P141751.3%
 
p140591.3%
 
A126591.1%
 
s126141.1%
 
y122331.1%
 
M115351.0%
 
t91430.8%
 
u81700.7%
 
I42140.4%
 
m39130.4%
 
.38250.3%
 
g26100.2%
 
f25550.2%
 
C25150.2%
 
R17620.2%
 
Other values (25)158851.4%
 

Most frequent None characters

ValueCountFrequency (%) 
ó293689.2%
 
í35710.8%
 

Parent4Name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct62
Distinct (%)0.6%
Missing201692
Missing (%)95.1%
Memory size1.6 MiB
Market Price Support (MPS)
4875 
Market Price Support (MPS) Non MPS commodities
 
385
Market Price Support (MPS) Beef and Veal
 
384
Market Price Support (MPS) Milk
 
374
Market Price Support (MPS) Poultry Meat
 
371
Other values (57)
4033 
ValueCountFrequency (%) 
Market Price Support (MPS)48752.3%
 
Market Price Support (MPS) Non MPS commodities3850.2%
 
Market Price Support (MPS) Beef and Veal3840.2%
 
Market Price Support (MPS) Milk3740.2%
 
Market Price Support (MPS) Poultry Meat3710.2%
 
Market Price Support (MPS) Pigmeat3640.2%
 
Market Price Support (MPS) Maize3230.2%
 
Market Price Support (MPS) Rice2950.1%
 
Market Price Support (MPS) Refined Sugar2880.1%
 
Market Price Support (MPS) Eggs2320.1%
 
Market Price Support (MPS) Soybeans2000.1%
 
Market Price Support (MPS) Wheat1900.1%
 
Market Price Support (MPS) Coffee1770.1%
 
Market Price Support (MPS) Barley1400.1%
 
Market Price Support (MPS) Tomatoes1290.1%
 
Market Price Support (MPS) Bananas1270.1%
 
Market Price Support (MPS) Potatoes1230.1%
 
Market Price Support (MPS) Beans1130.1%
 
Market Price Support (MPS) Sorghum84< 0.1%
 
Market Price Support (MPS) Sheep Meat84< 0.1%
 
Market Price Support (MPS) Oats66< 0.1%
 
Market Price Support (MPS) Rapeseed66< 0.1%
 
Market Price Support (MPS) Cotton65< 0.1%
 
Market Price Support (MPS) Palm Oil60< 0.1%
 
Market Price Support (MPS) Flowers60< 0.1%
 
Other values (37)8470.4%
 
(Missing)20169295.1%
 
2020-12-12T15:22:11.045354image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:11.122420image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length51
Median length3
Mean length4.455618205
Min length3

Overview of Unicode Properties

Unique unicode characters46
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40553042.9%
 
a21652722.9%
 
560155.9%
 
r325663.4%
 
e270152.9%
 
t234662.5%
 
M224022.4%
 
P223472.4%
 
S219662.3%
 
p212142.2%
 
o135641.4%
 
i131581.4%
 
u113571.2%
 
c112161.2%
 
k108021.1%
 
(104221.1%
 
)104221.1%
 
s21600.2%
 
l17970.2%
 
m15560.2%
 
g12620.1%
 
d12570.1%
 
f10940.1%
 
B8440.1%
 
y7620.1%
 
Other values (21)43780.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter79762184.4%
 
Uppercase Letter706197.5%
 
Space Separator560155.9%
 
Open Punctuation104221.1%
 
Close Punctuation104221.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40553050.8%
 
a21652727.1%
 
r325664.1%
 
e270153.4%
 
t234662.9%
 
p212142.7%
 
o135641.7%
 
i131581.6%
 
u113571.4%
 
c112161.4%
 
k108021.4%
 
s21600.3%
 
l17970.2%
 
m15560.2%
 
g12620.2%
 
d12570.2%
 
f10940.1%
 
y7620.1%
 
h4940.1%
 
z323< 0.1%
 
b251< 0.1%
 
w141< 0.1%
 
v76< 0.1%
 
x33< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M2240231.7%
 
P2234731.6%
 
S2196631.1%
 
B8441.2%
 
R6700.9%
 
V4060.6%
 
C3910.6%
 
N3850.5%
 
W3220.5%
 
E2320.3%
 
O1580.2%
 
T1290.2%
 
F1150.2%
 
A830.1%
 
D660.1%
 
G380.1%
 
L33< 0.1%
 
Y20< 0.1%
 
H12< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
56015100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(10422100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)10422100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin86824091.9%
 
Common768598.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40553046.7%
 
a21652724.9%
 
r325663.8%
 
e270153.1%
 
t234662.7%
 
M224022.6%
 
P223472.6%
 
S219662.5%
 
p212142.4%
 
o135641.6%
 
i131581.5%
 
u113571.3%
 
c112161.3%
 
k108021.2%
 
s21600.2%
 
l17970.2%
 
m15560.2%
 
g12620.1%
 
d12570.1%
 
f10940.1%
 
B8440.1%
 
y7620.1%
 
R6700.1%
 
h4940.1%
 
V406< 0.1%
 
Other values (18)28080.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
5601572.9%
 
(1042213.6%
 
)1042213.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII945099100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40553042.9%
 
a21652722.9%
 
560155.9%
 
r325663.4%
 
e270152.9%
 
t234662.5%
 
M224022.4%
 
P223472.4%
 
S219662.3%
 
p212142.2%
 
o135641.4%
 
i131581.4%
 
u113571.2%
 
c112161.2%
 
k108021.1%
 
(104221.1%
 
)104221.1%
 
s21600.2%
 
l17970.2%
 
m15560.2%
 
g12620.1%
 
d12570.1%
 
f10940.1%
 
B8440.1%
 
y7620.1%
 
Other values (21)43780.5%
 

Parent4Name_es
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)0.6%
Missing201692
Missing (%)95.1%
Memory size1.6 MiB
Apoyo al Precio de Mercado
4182 
Apoyo al Precio de Mercado (APM)
693 
Market Price Support (MPS) Productos No APM
 
385
Market Price Support (MPS) Carne Vacuna
 
384
Market Price Support (MPS) Leche
 
374
Other values (58)
4404 
ValueCountFrequency (%) 
Apoyo al Precio de Mercado41822.0%
 
Apoyo al Precio de Mercado (APM)6930.3%
 
Market Price Support (MPS) Productos No APM3850.2%
 
Market Price Support (MPS) Carne Vacuna3840.2%
 
Market Price Support (MPS) Leche3740.2%
 
Market Price Support (MPS) Carne de Pollo3710.2%
 
Market Price Support (MPS) Carne de Cerdo3640.2%
 
Market Price Support (MPS) Maíz3230.2%
 
Market Price Support (MPS) Arroz2950.1%
 
Market Price Support (MPS) Azúcar Refinada2880.1%
 
Market Price Support (MPS) Huevo2320.1%
 
Market Price Support (MPS) Soja2000.1%
 
Market Price Support (MPS) Trigo1900.1%
 
Market Price Support (MPS) Café1770.1%
 
Market Price Support (MPS) Cebada1400.1%
 
Market Price Support (MPS) Tomate1290.1%
 
Market Price Support (MPS) Banano1270.1%
 
Market Price Support (MPS) Papa1230.1%
 
Market Price Support (MPS) Frijol1130.1%
 
Market Price Support (MPS) Carne de Oveja84< 0.1%
 
Market Price Support (MPS) Sorgo84< 0.1%
 
Market Price Support (MPS) Colza66< 0.1%
 
Market Price Support (MPS) Avena66< 0.1%
 
Market Price Support (MPS) Algodón65< 0.1%
 
Market Price Support (MPS) Aceite de Palma60< 0.1%
 
Other values (38)9070.4%
 
(Missing)20169295.1%
 
2020-12-12T15:22:11.201989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:11.276553image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length48
Median length3
Mean length4.476644634
Min length3

Overview of Unicode Properties

Unique unicode characters52
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40609042.8%
 
a22280123.5%
 
623866.6%
 
e304293.2%
 
r299913.2%
 
o294803.1%
 
P180971.9%
 
M174611.8%
 
c169651.8%
 
p161021.7%
 
t119661.3%
 
d119121.3%
 
S114111.2%
 
i113831.2%
 
A68060.7%
 
u67780.7%
 
(62400.7%
 
)62400.7%
 
l62100.7%
 
k55470.6%
 
y49090.5%
 
C20800.2%
 
z10690.1%
 
s5810.1%
 
j4990.1%
 
Other values (27)61260.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter81594885.9%
 
Space Separator623866.6%
 
Uppercase Letter587456.2%
 
Open Punctuation62400.7%
 
Close Punctuation62400.7%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40609049.8%
 
a22280127.3%
 
e304293.7%
 
r299913.7%
 
o294803.6%
 
c169652.1%
 
p161022.0%
 
t119661.5%
 
d119121.5%
 
i113831.4%
 
u67780.8%
 
l62100.8%
 
k55470.7%
 
y49090.6%
 
z10690.1%
 
s5810.1%
 
j4990.1%
 
g4860.1%
 
f4730.1%
 
v4150.1%
 
h380< 0.1%
 
í323< 0.1%
 
m310< 0.1%
 
ú288< 0.1%
 
é177< 0.1%
 
Other values (4)384< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P1809730.8%
 
M1746129.7%
 
S1141119.4%
 
A680611.6%
 
C20803.5%
 
L4730.8%
 
V4390.7%
 
N4120.7%
 
T3850.7%
 
R2880.5%
 
H2320.4%
 
F2160.4%
 
B1530.3%
 
G880.1%
 
O840.1%
 
U330.1%
 
D330.1%
 
Y300.1%
 
Ñ20< 0.1%
 
E4< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
62386100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(6240100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)6240100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin87469392.1%
 
Common748667.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40609046.4%
 
a22280125.5%
 
e304293.5%
 
r299913.4%
 
o294803.4%
 
P180972.1%
 
M174612.0%
 
c169651.9%
 
p161021.8%
 
t119661.4%
 
d119121.4%
 
S114111.3%
 
i113831.3%
 
A68060.8%
 
u67780.8%
 
l62100.7%
 
k55470.6%
 
y49090.6%
 
C20800.2%
 
z10690.1%
 
s5810.1%
 
j4990.1%
 
g4860.1%
 
f4730.1%
 
L4730.1%
 
Other values (24)46940.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
6238683.3%
 
(62408.3%
 
)62408.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII94851899.9%
 
None10410.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40609042.8%
 
a22280123.5%
 
623866.6%
 
e304293.2%
 
r299913.2%
 
o294803.1%
 
P180971.9%
 
M174611.8%
 
c169651.8%
 
p161021.7%
 
t119661.3%
 
d119121.3%
 
S114111.2%
 
i113831.2%
 
A68060.7%
 
u67780.7%
 
(62400.7%
 
)62400.7%
 
l62100.7%
 
k55470.6%
 
y49090.5%
 
C20800.2%
 
z10690.1%
 
s5810.1%
 
j4990.1%
 
Other values (20)50850.5%
 

Most frequent None characters

ValueCountFrequency (%) 
í32331.0%
 
ú28827.7%
 
é17717.0%
 
ó10610.2%
 
á827.9%
 
ñ454.3%
 
Ñ201.9%
 

ind_id
Real number (ℝ≥0)

Distinct103
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean31.60916115
Minimum0
Maximum188
Zeros592
Zeros (%)0.3%
Memory size1.6 MiB
2020-12-12T15:22:11.351117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median18
Q329
95-th percentile137
Maximum188
Range188
Interquartile range (IQR)20

Descriptive statistics

Standard deviation41.98351573
Coefficient of variation (CV)1.328207209
Kurtosis4.152272306
Mean31.60916115
Median Absolute Deviation (MAD)10
Skewness2.247393769
Sum6704714
Variance1762.615593
MonotocityNot monotonic
2020-12-12T15:22:11.428684image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
17110095.2%
 
3109065.1%
 
1100734.7%
 
1992224.3%
 
2454592.6%
 
3354522.6%
 
2354522.6%
 
10653502.5%
 
1452482.5%
 
251972.5%
 
2751972.5%
 
1051952.4%
 
1851952.4%
 
651952.4%
 
751952.4%
 
851952.4%
 
451952.4%
 
1151942.4%
 
1351922.4%
 
1651852.4%
 
1251302.4%
 
2051262.4%
 
2151112.4%
 
2251112.4%
 
550982.4%
 
Other values (78)6123128.9%
 
ValueCountFrequency (%) 
05920.3%
 
1100734.7%
 
251972.5%
 
3109065.1%
 
451952.4%
 
550982.4%
 
651952.4%
 
751952.4%
 
851952.4%
 
950942.4%
 
ValueCountFrequency (%) 
18846< 0.1%
 
1873990.2%
 
1863990.2%
 
1853470.2%
 
1842710.1%
 
1833760.2%
 
1823550.2%
 
1813230.2%
 
1803240.2%
 
1793940.2%
 

description
Categorical

HIGH CARDINALITY

Distinct108
Distinct (%)0.1%
Missing592
Missing (%)0.3%
Memory size1.6 MiB
Market Price Support (MPS)
 
11009
Value of Production (at farm gate)
 
10906
Level of Production
 
10073
Payments based on output
 
9608
Support based on commodity outputs
 
5858
Other values (103)
164068 
ValueCountFrequency (%) 
Market Price Support (MPS)110095.2%
 
Value of Production (at farm gate)109065.1%
 
Level of Production100734.7%
 
Payments based on output96084.5%
 
Support based on commodity outputs58582.8%
 
Payments based on input use55962.6%
 
Excess Feed Cost54672.6%
 
Variable input use54672.6%
 
Producer NPC54662.6%
 
% Producer Single Commodity Transfers54522.6%
 
Producer Single Commodity Transfers54522.6%
 
Consumer NPC53822.5%
 
Market Price Support53502.5%
 
Transfers to Producers From Taxpayers52482.5%
 
Fixed capital formation52382.5%
 
On-farm services52092.5%
 
Producer Price (at farm gate)51972.5%
 
Market Price Differential51952.4%
 
Value of Consumption (at farm gate)51952.4%
 
Level of Consumption51952.4%
 
Reference Price (at farm gate)51952.4%
 
Transfers to Producers From Consumers51952.4%
 
Other Transfers From Consumers51942.4%
 
Budgetary Transfers51922.4%
 
Consumer Single Commodity Transfers (CSCT)51112.4%
 
Other values (83)5807227.4%
 
2020-12-12T15:22:11.518761image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:11.603835image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length73
Median length28
Mean length28.94702377
Min length3

Overview of Unicode Properties

Unique unicode characters59
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
68813611.2%
 
e5536679.0%
 
r5077968.3%
 
o4338337.1%
 
t3877716.3%
 
a3539845.8%
 
s3322905.4%
 
n3263905.3%
 
u2655534.3%
 
i2362523.8%
 
m2092793.4%
 
c1788962.9%
 
d1698062.8%
 
P1591222.6%
 
f1544932.5%
 
p1391012.3%
 
l942301.5%
 
C857191.4%
 
y777371.3%
 
g675971.1%
 
T646761.1%
 
S646431.1%
 
(615491.0%
 
)615491.0%
 
b467450.8%
 
Other values (34)4192556.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter464024675.6%
 
Space Separator68813611.2%
 
Uppercase Letter6015169.8%
 
Open Punctuation615491.0%
 
Close Punctuation615491.0%
 
Other Punctuation608931.0%
 
Dash Punctuation223550.4%
 
Decimal Number38250.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P15912226.5%
 
C8571914.3%
 
T6467610.8%
 
S6464310.7%
 
M406276.8%
 
F284694.7%
 
A245834.1%
 
V231643.9%
 
N226233.8%
 
R171722.9%
 
L163312.7%
 
I131842.2%
 
E120212.0%
 
O115031.9%
 
D56340.9%
 
B55280.9%
 
J17830.3%
 
G16610.3%
 
H15210.3%
 
K11380.2%
 
W3990.1%
 
U15< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e55366711.9%
 
r50779610.9%
 
o4338339.3%
 
t3877718.4%
 
a3539847.6%
 
s3322907.2%
 
n3263907.0%
 
u2655535.7%
 
i2362525.1%
 
m2092794.5%
 
c1788963.9%
 
d1698063.7%
 
f1544933.3%
 
p1391013.0%
 
l942302.0%
 
y777371.7%
 
g675971.5%
 
b467451.0%
 
v316560.7%
 
k291450.6%
 
x217200.5%
 
q105660.2%
 
h99830.2%
 
w1756< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
688136100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(61549100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)61549100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/3169852.1%
 
,1680627.6%
 
.613910.1%
 
%58519.6%
 
:3990.7%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-22355100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1142137.2%
 
2141437.0%
 
367017.5%
 
43208.4%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin524176285.4%
 
Common89830714.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e55366710.6%
 
r5077969.7%
 
o4338338.3%
 
t3877717.4%
 
a3539846.8%
 
s3322906.3%
 
n3263906.2%
 
u2655535.1%
 
i2362524.5%
 
m2092794.0%
 
c1788963.4%
 
d1698063.2%
 
P1591223.0%
 
f1544932.9%
 
p1391012.7%
 
l942301.8%
 
C857191.6%
 
y777371.5%
 
g675971.3%
 
T646761.2%
 
S646431.2%
 
b467450.9%
 
M406270.8%
 
v316560.6%
 
k291450.6%
 
Other values (21)2307544.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
68813676.6%
 
(615496.9%
 
)615496.9%
 
/316983.5%
 
-223552.5%
 
,168061.9%
 
.61390.7%
 
%58510.7%
 
114210.2%
 
214140.2%
 
36700.1%
 
:399< 0.1%
 
4320< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII6140069100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
68813611.2%
 
e5536679.0%
 
r5077968.3%
 
o4338337.1%
 
t3877716.3%
 
a3539845.8%
 
s3322905.4%
 
n3263905.3%
 
u2655534.3%
 
i2362523.8%
 
m2092793.4%
 
c1788962.9%
 
d1698062.8%
 
P1591222.6%
 
f1544932.5%
 
p1391012.3%
 
l942301.5%
 
C857191.4%
 
y777371.3%
 
g675971.1%
 
T646761.1%
 
S646431.1%
 
(615491.0%
 
)615491.0%
 
b467450.8%
 
Other values (34)4192556.8%
 

description_es
Categorical

HIGH CARDINALITY

Distinct102
Distinct (%)< 0.1%
Missing1197
Missing (%)0.6%
Memory size1.6 MiB
Valor de Producción (en finca)
 
10906
Nivel de Producción
 
10073
Pagos Basados en la Producción
 
9608
Apoyo al Precio de Mercado (APM)
 
9025
Apoyo al Precio de Mercado
 
7334
Other values (97)
163971 
ValueCountFrequency (%) 
Valor de Producción (en finca)109065.1%
 
Nivel de Producción100734.7%
 
Pagos Basados en la Producción96084.5%
 
Apoyo al Precio de Mercado (APM)90254.3%
 
Apoyo al Precio de Mercado73343.5%
 
Uso de Insumos Variables54672.6%
 
CPN del Productor54662.6%
 
Apoyo Basados en la Producción de Productos54592.6%
 
Transferencias al Productor de un Producto Individual54522.6%
 
Transferencias al Productor de un Producto Individual (%)54522.6%
 
Transferencias a los Productores de los Contribuyentes52482.5%
 
Formación de Capital Fijo52382.5%
 
Servicios en finca52092.5%
 
Precio al Productor (Precio en finca)51972.5%
 
Precio de Referencia (Precio en finca)51952.4%
 
Diferencial de Precio de Mercado51952.4%
 
Valor de Consumo (Precio en finca)51952.4%
 
Transferencias a los Productores de los Consumidores51952.4%
 
Nivel de Consumo51952.4%
 
Otras Transferencias de los Consumidores51942.4%
 
Transferencias Presupuestarias51922.4%
 
Exceso de Coste del Pienso51302.4%
 
Pagos Basados en la Producción por Tonelada51262.4%
 
Transferencias al Consumidor de un Producto Individual51112.4%
 
CPN del Consumidor51112.4%
 
Other values (77)5894427.8%
 
2020-12-12T15:22:11.692411image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:11.777484image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length86
Median length32
Mean length35.63112289
Min length3

Overview of Unicode Properties

Unique unicode characters62
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
92482112.2%
 
e6685718.8%
 
o6657188.8%
 
a5241826.9%
 
r4994626.6%
 
s4708356.2%
 
d4574636.1%
 
n4509146.0%
 
c4259065.6%
 
i4041825.3%
 
u2723473.6%
 
P2475893.3%
 
l2265433.0%
 
t1361111.8%
 
f1018481.3%
 
C804061.1%
 
m793531.0%
 
ó676450.9%
 
A636570.8%
 
T587180.8%
 
(585580.8%
 
)585580.8%
 
p552820.7%
 
v517410.7%
 
I482780.6%
 
Other values (37)4591726.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter569311875.3%
 
Space Separator92482112.2%
 
Uppercase Letter7424239.8%
 
Other Punctuation610750.8%
 
Open Punctuation585580.8%
 
Close Punctuation585580.8%
 
Dash Punctuation152110.2%
 
Decimal Number40960.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P24758933.3%
 
C8040610.8%
 
A636578.6%
 
T587187.9%
 
I482786.5%
 
N442896.0%
 
M390155.3%
 
V340014.6%
 
B326114.4%
 
R184012.5%
 
S180662.4%
 
E119931.6%
 
F111531.5%
 
G108321.5%
 
O68880.9%
 
U58810.8%
 
D56070.8%
 
J17830.2%
 
H14950.2%
 
K10410.1%
 
L7190.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e66857111.7%
 
o66571811.7%
 
a5241829.2%
 
r4994628.8%
 
s4708358.3%
 
d4574638.0%
 
n4509147.9%
 
c4259067.5%
 
i4041827.1%
 
u2723474.8%
 
l2265434.0%
 
t1361112.4%
 
f1018481.8%
 
m793531.4%
 
ó676451.2%
 
p552821.0%
 
v517410.9%
 
y381180.7%
 
g360400.6%
 
b260300.5%
 
q108900.2%
 
á94640.2%
 
j67890.1%
 
x51300.1%
 
í1701< 0.1%
 
Other values (3)853< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
924821100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(58558100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)58558100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/3169851.9%
 
,1711628.0%
 
.641010.5%
 
%54528.9%
 
:3990.7%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1142134.7%
 
2141434.5%
 
394123.0%
 
43207.8%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-15211100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin643554185.2%
 
Common112231914.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e66857110.4%
 
o66571810.3%
 
a5241828.1%
 
r4994627.8%
 
s4708357.3%
 
d4574637.1%
 
n4509147.0%
 
c4259066.6%
 
i4041826.3%
 
u2723474.2%
 
P2475893.8%
 
l2265433.5%
 
t1361112.1%
 
f1018481.6%
 
C804061.2%
 
m793531.2%
 
ó676451.1%
 
A636571.0%
 
T587180.9%
 
p552820.9%
 
v517410.8%
 
I482780.8%
 
N442890.7%
 
M390150.6%
 
y381180.6%
 
Other values (24)2573684.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
92482182.4%
 
(585585.2%
 
)585585.2%
 
/316982.8%
 
,171161.5%
 
-152111.4%
 
.64100.6%
 
%54520.5%
 
114210.1%
 
214140.1%
 
39410.1%
 
:399< 0.1%
 
4320< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII747898199.0%
 
None788791.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
92482112.4%
 
e6685718.9%
 
o6657188.9%
 
a5241827.0%
 
r4994626.7%
 
s4708356.3%
 
d4574636.1%
 
n4509146.0%
 
c4259065.7%
 
i4041825.4%
 
u2723473.6%
 
P2475893.3%
 
l2265433.0%
 
t1361111.8%
 
f1018481.4%
 
C804061.1%
 
m793531.1%
 
A636570.9%
 
T587180.8%
 
(585580.8%
 
)585580.8%
 
p552820.7%
 
v517410.7%
 
I482780.6%
 
N442890.6%
 
Other values (33)4036495.4%
 

Most frequent None characters

ValueCountFrequency (%) 
ó6764585.8%
 
á946412.0%
 
í17012.2%
 
ú690.1%
 

code
Categorical

HIGH CARDINALITY

Distinct147
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
VP
 
11305
MPS
 
10779
QP
 
10073
PO
 
9608
CO
 
5858
Other values (142)
164491 
ValueCountFrequency (%) 
VP113055.3%
 
MPS107795.1%
 
QP100734.7%
 
PO96084.5%
 
CO58582.8%
 
PI55962.6%
 
VC55942.6%
 
TPC55422.6%
 
OTC55412.6%
 
PIV54672.6%
 
EFC54672.6%
 
PNPC54662.6%
 
PSCT54522.6%
 
PSCTP54522.6%
 
CNPC53822.5%
 
TCTC53652.5%
 
TPT52482.5%
 
PIF52382.5%
 
PIS52092.5%
 
PP51972.5%
 
QC51952.4%
 
MPD51952.4%
 
RP51952.4%
 
BT51922.4%
 
LV51852.4%
 
Other values (122)5731327.0%
 
2020-12-12T15:22:11.867562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:11.940124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length3
Mean length2.934747353
Min length2

Overview of Unicode Properties

Unique unicode characters25
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
P16205926.0%
 
C10301116.5%
 
T7001911.2%
 
S586199.4%
 
V321985.2%
 
O318085.1%
 
M228413.7%
 
I218833.5%
 
E184343.0%
 
Q153782.5%
 
N138492.2%
 
F119551.9%
 
R118911.9%
 
B98341.6%
 
L95381.5%
 
G78021.3%
 
D67411.1%
 
A58770.9%
 
H55130.9%
 
114230.2%
 
K7380.1%
 
X3850.1%
 
U3570.1%
 
W3220.1%
 
Y26< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter62107899.8%
 
Decimal Number14230.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P16205926.1%
 
C10301116.6%
 
T7001911.3%
 
S586199.4%
 
V321985.2%
 
O318085.1%
 
M228413.7%
 
I218833.5%
 
E184343.0%
 
Q153782.5%
 
N138492.2%
 
F119551.9%
 
R118911.9%
 
B98341.6%
 
L95381.5%
 
G78021.3%
 
D67411.1%
 
A58770.9%
 
H55130.9%
 
K7380.1%
 
X3850.1%
 
U3570.1%
 
W3220.1%
 
Y26< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
11423100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin62107899.8%
 
Common14230.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
P16205926.1%
 
C10301116.6%
 
T7001911.3%
 
S586199.4%
 
V321985.2%
 
O318085.1%
 
M228413.7%
 
I218833.5%
 
E184343.0%
 
Q153782.5%
 
N138492.2%
 
F119551.9%
 
R118911.9%
 
B98341.6%
 
L95381.5%
 
G78021.3%
 
D67411.1%
 
A58770.9%
 
H55130.9%
 
K7380.1%
 
X3850.1%
 
U3570.1%
 
W3220.1%
 
Y26< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
11423100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII622501100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
P16205926.0%
 
C10301116.5%
 
T7001911.2%
 
S586199.4%
 
V321985.2%
 
O318085.1%
 
M228413.7%
 
I218833.5%
 
E184343.0%
 
Q153782.5%
 
N138492.2%
 
F119551.9%
 
R118911.9%
 
B98341.6%
 
L95381.5%
 
G78021.3%
 
D67411.1%
 
A58770.9%
 
H55130.9%
 
114230.2%
 
K7380.1%
 
X3850.1%
 
U3570.1%
 
W3220.1%
 
Y26< 0.1%
 

comm_id
Real number (ℝ≥0)

ZEROS

Distinct62
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5827621
Minimum0
Maximum108
Zeros23429
Zeros (%)11.0%
Memory size1.6 MiB
2020-12-12T15:22:12.011686image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median26
Q336
95-th percentile63
Maximum108
Range108
Interquartile range (IQR)30

Descriptive statistics

Standard deviation21.29432557
Coefficient of variation (CV)0.8323700737
Kurtosis2.235582886
Mean25.5827621
Median Absolute Deviation (MAD)13
Skewness1.20488625
Sum5426462
Variance453.4483017
MonotocityNot monotonic
2020-12-12T15:22:12.093756image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
02342911.0%
 
4135836.4%
 
20132916.3%
 
31131086.2%
 
26129996.1%
 
19115355.4%
 
32102974.9%
 
34102474.8%
 
1383033.9%
 
3673183.5%
 
4969663.3%
 
861792.9%
 
351242.4%
 
4445332.1%
 
2844782.1%
 
5043552.1%
 
642882.0%
 
541462.0%
 
3930201.4%
 
3829721.4%
 
3324421.2%
 
2224421.2%
 
923811.1%
 
1422201.0%
 
3720351.0%
 
Other values (37)3042314.3%
 
ValueCountFrequency (%) 
02342911.0%
 
110730.5%
 
216650.8%
 
351242.4%
 
4135836.4%
 
541462.0%
 
642882.0%
 
861792.9%
 
923811.1%
 
1112210.6%
 
ValueCountFrequency (%) 
10810730.5%
 
10710730.5%
 
10610730.5%
 
981740.1%
 
971740.1%
 
961740.1%
 
951400.1%
 
857730.4%
 
7812210.6%
 
7712210.6%
 

Category
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
2
117592 
3
65513 
1
29009 
ValueCountFrequency (%) 
211759255.4%
 
36551330.9%
 
12900913.7%
 
2020-12-12T15:22:12.165818image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:12.204351image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:12.252393image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
211759255.4%
 
36551330.9%
 
12900913.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number212114100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
211759255.4%
 
36551330.9%
 
12900913.7%
 

Most occurring scripts

ValueCountFrequency (%) 
Common212114100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
211759255.4%
 
36551330.9%
 
12900913.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII212114100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
211759255.4%
 
36551330.9%
 
12900913.7%
 

unit
Categorical

HIGH CARDINALITY

Distinct116
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
EURmn
19998 
USDmn
18879 
CADmn
16434 
MXNmn
15576 
000t
15378 
Other values (111)
125849 
ValueCountFrequency (%) 
EURmn199989.4%
 
USDmn188798.9%
 
CADmn164347.7%
 
MXNmn155767.3%
 
000t153787.2%
 
CLPmn136016.4%
 
ratio116725.5%
 
COPmn112595.3%
 
BRLmn87124.1%
 
CRCmn80643.8%
 
%77523.7%
 
ARSmn73483.5%
 
DOPmn40081.9%
 
GTQmn38541.8%
 
JMDmn30361.4%
 
SVCmn29561.4%
 
EUR/t26401.2%
 
USD/t24121.1%
 
PYGmn22021.0%
 
CAD/t21121.0%
 
PENmn20461.0%
 
MXN/t19800.9%
 
UYUmn19360.9%
 
SRDmn19360.9%
 
NIOmn18900.9%
 
Other values (91)2443311.5%
 
2020-12-12T15:22:12.336465image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:12.417034image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length5
Mean length4.800390356
Min length1

Overview of Unicode Properties

Unique unicode characters39
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n15621315.3%
 
m15618715.3%
 
C681396.7%
 
D573205.6%
 
R521425.1%
 
U486584.8%
 
t477354.7%
 
0461344.5%
 
P396793.9%
 
S356103.5%
 
A306863.0%
 
L277472.7%
 
E250942.5%
 
N244722.4%
 
/214982.1%
 
M211802.1%
 
O205842.0%
 
B178201.8%
 
X176221.7%
 
r120971.2%
 
o120971.2%
 
a116721.1%
 
i116721.1%
 
T105351.0%
 
G98291.0%
 
Other values (14)358083.5%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter53344752.4%
 
Lowercase Letter40939940.2%
 
Decimal Number461344.5%
 
Other Punctuation292502.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C6813912.8%
 
D5732010.7%
 
R521429.8%
 
U486589.1%
 
P396797.4%
 
S356106.7%
 
A306865.8%
 
L277475.2%
 
E250944.7%
 
N244724.6%
 
M211804.0%
 
O205843.9%
 
B178203.3%
 
X176223.3%
 
T105352.0%
 
G98291.8%
 
Y57721.1%
 
H51851.0%
 
Q46220.9%
 
J35580.7%
 
V32670.6%
 
I22750.4%
 
Z12520.2%
 
K3990.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/2149873.5%
 
%775226.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n15621338.2%
 
m15618738.2%
 
t4773511.7%
 
r120973.0%
 
o120973.0%
 
a116722.9%
 
i116722.9%
 
p4250.1%
 
e4250.1%
 
s4250.1%
 
q3990.1%
 
l52< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
046134100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin94284692.6%
 
Common753847.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n15621316.6%
 
m15618716.6%
 
C681397.2%
 
D573206.1%
 
R521425.5%
 
U486585.2%
 
t477355.1%
 
P396794.2%
 
S356103.8%
 
A306863.3%
 
L277472.9%
 
E250942.7%
 
N244722.6%
 
M211802.2%
 
O205842.2%
 
B178201.9%
 
X176221.9%
 
r120971.3%
 
o120971.3%
 
a116721.2%
 
i116721.2%
 
T105351.1%
 
G98291.0%
 
Y57720.6%
 
H51850.5%
 
Other values (11)170991.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
04613461.2%
 
/2149828.5%
 
%775210.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1018230100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n15621315.3%
 
m15618715.3%
 
C681396.7%
 
D573205.6%
 
R521425.1%
 
U486584.8%
 
t477354.7%
 
0461344.5%
 
P396793.9%
 
S356103.5%
 
A306863.0%
 
L277472.7%
 
E250942.5%
 
N244722.4%
 
/214982.1%
 
M211802.1%
 
O205842.0%
 
B178201.8%
 
X176221.7%
 
r120971.2%
 
o120971.2%
 
a116721.1%
 
i116721.1%
 
T105351.0%
 
G98291.0%
 
Other values (14)358083.5%
 

year
Real number (ℝ≥0)

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.568902
Minimum1986
Maximum2018
Zeros0
Zeros (%)0.0%
Memory size1.6 MiB
2020-12-12T15:22:12.481590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1986
5-th percentile1989
Q11999
median2008
Q32013
95-th percentile2017
Maximum2018
Range32
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.622613975
Coefficient of variation (CV)0.004299335699
Kurtosis-0.7695075152
Mean2005.568902
Median Absolute Deviation (MAD)6
Skewness-0.561523344
Sum425409242
Variance74.34947176
MonotocityNot monotonic
2020-12-12T15:22:12.549148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
2011123615.8%
 
2012123135.8%
 
2013120835.7%
 
2014113345.3%
 
2010112155.3%
 
200994154.4%
 
201592984.4%
 
201684454.0%
 
200882693.9%
 
200782193.9%
 
200679853.8%
 
201774773.5%
 
200053792.5%
 
201853782.5%
 
199953782.5%
 
200153782.5%
 
200253782.5%
 
200353782.5%
 
200453782.5%
 
200553782.5%
 
199853772.5%
 
199753772.5%
 
199649302.3%
 
199549302.3%
 
199439941.9%
 
Other values (8)2606712.3%
 
ValueCountFrequency (%) 
198628031.3%
 
198728031.3%
 
198828031.3%
 
198928031.3%
 
199034331.6%
 
199134341.6%
 
199239941.9%
 
199339941.9%
 
199439941.9%
 
199549302.3%
 
ValueCountFrequency (%) 
201853782.5%
 
201774773.5%
 
201684454.0%
 
201592984.4%
 
2014113345.3%
 
2013120835.7%
 
2012123135.8%
 
2011123615.8%
 
2010112155.3%
 
200994154.4%
 

value
Real number (ℝ)

SKEWED
ZEROS

Distinct79708
Distinct (%)37.6%
Missing220
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean72257.38726
Minimum-11057736.76
Maximum155509318.4
Zeros89201
Zeros (%)42.1%
Memory size1.6 MiB
2020-12-12T15:22:12.651736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-11057736.76
5-th percentile-0.437553861
Q10
median1
Q3708.425152
95-th percentile80108.04087
Maximum155509318.4
Range166567055.2
Interquartile range (IQR)708.425152

Descriptive statistics

Standard deviation1183173.761
Coefficient of variation (CV)16.3744332
Kurtosis5630.738653
Mean72257.38726
Median Absolute Deviation (MAD)1
Skewness61.62315453
Sum1.531090682e+10
Variance1.399900149e+12
MonotocityNot monotonic
2020-12-12T15:22:12.733807image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
08920142.1%
 
141321.9%
 
1.09890109940< 0.1%
 
1.138< 0.1%
 
1337< 0.1%
 
1.4630< 0.1%
 
1.1525< 0.1%
 
1.03524< 0.1%
 
921< 0.1%
 
0.96618357520< 0.1%
 
925.940420< 0.1%
 
1.026720< 0.1%
 
2820< 0.1%
 
12019< 0.1%
 
819< 0.1%
 
0.118< 0.1%
 
5018< 0.1%
 
14.517< 0.1%
 
20016< 0.1%
 
14016< 0.1%
 
40015< 0.1%
 
900015< 0.1%
 
31.5068493215< 0.1%
 
214< 0.1%
 
0.75757575814< 0.1%
 
Other values (79683)11807055.7%
 
(Missing)2200.1%
 
ValueCountFrequency (%) 
-11057736.761< 0.1%
 
-10647489.821< 0.1%
 
-10179309.891< 0.1%
 
-9806768.711< 0.1%
 
-9340644.3451< 0.1%
 
-9314016.311< 0.1%
 
-8932101.3011< 0.1%
 
-8735841.3081< 0.1%
 
-8370009.161< 0.1%
 
-8360591.5041< 0.1%
 
ValueCountFrequency (%) 
155509318.41< 0.1%
 
142003380.41< 0.1%
 
137797686.41< 0.1%
 
125152244.91< 0.1%
 
108832260.31< 0.1%
 
105203213.91< 0.1%
 
94934255.211< 0.1%
 
80734753.241< 0.1%
 
79117170.181< 0.1%
 
76777202.251< 0.1%
 

Commoditie
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct62
Distinct (%)< 0.1%
Missing130
Missing (%)0.1%
Memory size1.6 MiB
Group or not commodities
23299 
Beef and Veal
13583 
Milk
 
13291
Poultry Meat
 
13108
Pigmeat
 
12999
Other values (57)
135704 
ValueCountFrequency (%) 
Group or not commodities2329911.0%
 
Beef and Veal135836.4%
 
Milk132916.3%
 
Poultry Meat131086.2%
 
Pigmeat129996.1%
 
Maize115355.4%
 
Rice102974.9%
 
Refined Sugar102474.8%
 
Eggs83033.9%
 
Soybeans73183.5%
 
Wheat69663.3%
 
Coffee61792.9%
 
Barley51242.4%
 
Tomatoes45332.1%
 
Potatoes44782.1%
 
Non MPS commodities43552.1%
 
Bananas42882.0%
 
Beans41462.0%
 
Sorghum30201.4%
 
Sheep Meat29721.4%
 
Rapeseed24421.2%
 
Oats24421.2%
 
Cotton23811.1%
 
Flowers22201.0%
 
Sunflower20351.0%
 
Other values (37)3042314.3%
 
2020-12-12T15:22:12.831892image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:12.903954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length8
Mean length9.672977738
Min length3

Overview of Unicode Properties

Unique unicode characters44
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
e23293511.4%
 
o1999309.7%
 
a1580227.7%
 
1415726.9%
 
t1306606.4%
 
i1250916.1%
 
r930664.5%
 
s902674.4%
 
n897854.4%
 
m829904.0%
 
l663703.2%
 
d583992.8%
 
u566362.8%
 
M458812.2%
 
g449352.2%
 
P438732.1%
 
c419082.0%
 
f410732.0%
 
p363121.8%
 
S307201.5%
 
B296061.4%
 
y272871.3%
 
G246561.2%
 
R234231.1%
 
h178940.9%
 
Other values (19)1184835.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter163658579.8%
 
Uppercase Letter27361713.3%
 
Space Separator1415726.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M4588116.8%
 
P4387316.0%
 
S3072011.2%
 
B2960610.8%
 
G246569.0%
 
R234238.6%
 
V143975.3%
 
C134894.9%
 
W118504.3%
 
E83033.0%
 
O54592.0%
 
T45331.7%
 
N43551.6%
 
F42551.6%
 
A42071.5%
 
D24420.9%
 
L12210.4%
 
Y6050.2%
 
H3420.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e23293514.2%
 
o19993012.2%
 
a1580229.7%
 
t1306608.0%
 
i1250917.6%
 
r930665.7%
 
s902675.5%
 
n897855.5%
 
m829905.1%
 
l663704.1%
 
d583993.6%
 
u566363.5%
 
g449352.7%
 
c419082.6%
 
f410732.5%
 
p363122.2%
 
y272871.7%
 
h178941.1%
 
k134650.8%
 
z115350.7%
 
b92050.6%
 
w50280.3%
 
v25710.2%
 
x12210.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
141572100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin191020293.1%
 
Common1415726.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e23293512.2%
 
o19993010.5%
 
a1580228.3%
 
t1306606.8%
 
i1250916.5%
 
r930664.9%
 
s902674.7%
 
n897854.7%
 
m829904.3%
 
l663703.5%
 
d583993.1%
 
u566363.0%
 
M458812.4%
 
g449352.4%
 
P438732.3%
 
c419082.2%
 
f410732.2%
 
p363121.9%
 
S307201.6%
 
B296061.5%
 
y272871.4%
 
G246561.3%
 
R234231.2%
 
h178940.9%
 
V143970.8%
 
Other values (18)1040865.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
141572100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2051774100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
e23293511.4%
 
o1999309.7%
 
a1580227.7%
 
1415726.9%
 
t1306606.4%
 
i1250916.1%
 
r930664.5%
 
s902674.4%
 
n897854.4%
 
m829904.0%
 
l663703.2%
 
d583992.8%
 
u566362.8%
 
M458812.2%
 
g449352.2%
 
P438732.1%
 
c419082.0%
 
f410732.0%
 
p363121.8%
 
S307201.5%
 
B296061.4%
 
y272871.3%
 
G246561.2%
 
R234231.1%
 
h178940.9%
 
Other values (19)1184835.8%
 

Commoditie_es
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct62
Distinct (%)< 0.1%
Missing130
Missing (%)0.1%
Memory size1.6 MiB
Nulo
23299 
Carne Vacuna
13583 
Leche
 
13291
Carne de Pollo
 
13108
Carne de Cerdo
 
12999
Other values (57)
135704 
ValueCountFrequency (%) 
Nulo2329911.0%
 
Carne Vacuna135836.4%
 
Leche132916.3%
 
Carne de Pollo131086.2%
 
Carne de Cerdo129996.1%
 
Maíz115355.4%
 
Arroz102974.9%
 
Azúcar Refinada102474.8%
 
Huevo83033.9%
 
Soja73183.5%
 
Trigo69663.3%
 
Café61792.9%
 
Cebada51242.4%
 
Tomate45332.1%
 
Papa44782.1%
 
Productos No APM43552.1%
 
Banano42882.0%
 
Frijol41422.0%
 
Sorgo30201.4%
 
Carne de Oveja29721.4%
 
Avena24421.2%
 
Colza24421.2%
 
Algodón23811.1%
 
Flores22201.0%
 
Girasol20351.0%
 
Other values (37)3042714.3%
 
2020-12-12T15:22:12.983522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:13.061089image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length5
Mean length7.661370772
Min length3

Overview of Unicode Properties

Unique unicode characters49
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
a20785012.8%
 
e16737210.3%
 
o1522359.4%
 
r1181707.3%
 
1004626.2%
 
n962545.9%
 
C737634.5%
 
l728784.5%
 
d676104.2%
 
u578093.6%
 
c495763.1%
 
z380622.3%
 
A358212.2%
 
i341932.1%
 
P321482.0%
 
N284951.8%
 
t213831.3%
 
f191161.2%
 
M189981.2%
 
g176961.1%
 
j173761.1%
 
L169541.0%
 
V156181.0%
 
v149140.9%
 
T139410.9%
 
Other values (24)1363908.4%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter123581676.0%
 
Uppercase Letter28880617.8%
 
Space Separator1004626.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C7376325.5%
 
A3582112.4%
 
P3214811.1%
 
N284959.9%
 
M189986.6%
 
L169545.9%
 
V156185.4%
 
T139414.8%
 
S115594.0%
 
R102473.5%
 
H83032.9%
 
F76172.6%
 
B50611.8%
 
G32561.1%
 
O29721.0%
 
D12210.4%
 
U11970.4%
 
Y9060.3%
 
Ñ6050.2%
 
E124< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
a20785016.8%
 
e16737213.5%
 
o15223512.3%
 
r1181709.6%
 
n962547.8%
 
l728785.9%
 
d676105.5%
 
u578094.7%
 
c495764.0%
 
z380623.1%
 
i341932.8%
 
t213831.7%
 
f191161.5%
 
g176961.4%
 
j173761.4%
 
v149141.2%
 
h134651.1%
 
s115830.9%
 
í115350.9%
 
m106020.9%
 
ú102470.8%
 
é61790.5%
 
b54580.4%
 
p47760.4%
 
ó37900.3%
 
Other values (3)56870.5%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
100462100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin152462293.8%
 
Common1004626.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
a20785013.6%
 
e16737211.0%
 
o15223510.0%
 
r1181707.8%
 
n962546.3%
 
C737634.8%
 
l728784.8%
 
d676104.4%
 
u578093.8%
 
c495763.3%
 
z380622.5%
 
A358212.3%
 
i341932.2%
 
P321482.1%
 
N284951.9%
 
t213831.4%
 
f191161.3%
 
M189981.2%
 
g176961.2%
 
j173761.1%
 
L169541.1%
 
V156181.0%
 
v149141.0%
 
T139410.9%
 
h134650.9%
 
Other values (23)1229258.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
100462100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII158820397.7%
 
None368812.3%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
a20785013.1%
 
e16737210.5%
 
o1522359.6%
 
r1181707.4%
 
1004626.3%
 
n962546.1%
 
C737634.6%
 
l728784.6%
 
d676104.3%
 
u578093.6%
 
c495763.1%
 
z380622.4%
 
A358212.3%
 
i341932.2%
 
P321482.0%
 
N284951.8%
 
t213831.3%
 
f191161.2%
 
M189981.2%
 
g176961.1%
 
j173761.1%
 
L169541.1%
 
V156181.0%
 
v149140.9%
 
T139410.9%
 
Other values (17)995096.3%
 

Most frequent None characters

ValueCountFrequency (%) 
í1153531.3%
 
ú1024727.8%
 
é617916.8%
 
ó379010.3%
 
á29748.1%
 
ñ15514.2%
 
Ñ6051.6%
 

unitusd
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
USDmn
155788 
USD/t
20685 
000t
 
15378
ratio
 
11672
%
 
7752
Other values (5)
 
839
ValueCountFrequency (%) 
USDmn15578873.4%
 
USD/t206859.8%
 
000t153787.2%
 
ratio116725.5%
 
%77523.7%
 
USD/person3990.2%
 
USD/SqKmAL3470.2%
 
USD/SqKmAl52< 0.1%
 
person26< 0.1%
 
USD/USD15< 0.1%
 
2020-12-12T15:22:13.139156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T15:22:13.191701image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:13.267266image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length5
Mean length4.800390356
Min length1

Overview of Unicode Properties

Unique unicode characters21
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S17770017.5%
 
U17730117.4%
 
D17730117.4%
 
n15621315.3%
 
m15618715.3%
 
t477354.7%
 
0461344.5%
 
/214982.1%
 
r120971.2%
 
o120971.2%
 
a116721.1%
 
i116721.1%
 
%77520.8%
 
p425< 0.1%
 
e425< 0.1%
 
s425< 0.1%
 
q399< 0.1%
 
K399< 0.1%
 
A399< 0.1%
 
L347< 0.1%
 
l52< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter53344752.4%
 
Lowercase Letter40939940.2%
 
Decimal Number461344.5%
 
Other Punctuation292502.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S17770033.3%
 
U17730133.2%
 
D17730133.2%
 
K3990.1%
 
A3990.1%
 
L3470.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/2149873.5%
 
%775226.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n15621338.2%
 
m15618738.2%
 
t4773511.7%
 
r120973.0%
 
o120973.0%
 
a116722.9%
 
i116722.9%
 
p4250.1%
 
e4250.1%
 
s4250.1%
 
q3990.1%
 
l52< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
046134100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin94284692.6%
 
Common753847.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S17770018.8%
 
U17730118.8%
 
D17730118.8%
 
n15621316.6%
 
m15618716.6%
 
t477355.1%
 
r120971.3%
 
o120971.3%
 
a116721.2%
 
i116721.2%
 
p425< 0.1%
 
e425< 0.1%
 
s425< 0.1%
 
q399< 0.1%
 
K399< 0.1%
 
A399< 0.1%
 
L347< 0.1%
 
l52< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
04613461.2%
 
/2149828.5%
 
%775210.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1018230100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S17770017.5%
 
U17730117.4%
 
D17730117.4%
 
n15621315.3%
 
m15618715.3%
 
t477354.7%
 
0461344.5%
 
/214982.1%
 
r120971.2%
 
o120971.2%
 
a116721.1%
 
i116721.1%
 
%77520.8%
 
p425< 0.1%
 
e425< 0.1%
 
s425< 0.1%
 
q399< 0.1%
 
K399< 0.1%
 
A399< 0.1%
 
L347< 0.1%
 
l52< 0.1%
 

valueusd
Real number (ℝ)

SKEWED
ZEROS

Distinct80304
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2417.98381
Minimum-94866.86851
Maximum6780906
Zeros89421
Zeros (%)42.2%
Memory size1.6 MiB
2020-12-12T15:22:13.361848image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-94866.86851
5-th percentile-0.1677436218
Q10
median0.6935488935
Q3170.7507744
95-th percentile4835.884997
Maximum6780906
Range6875772.869
Interquartile range (IQR)170.7507744

Descriptive statistics

Standard deviation50734.45856
Coefficient of variation (CV)20.98213328
Kurtosis9516.52596
Mean2417.98381
Median Absolute Deviation (MAD)0.6935488935
Skewness87.85401746
Sum512888217.8
Variance2573985286
MonotocityNot monotonic
2020-12-12T15:22:13.444919image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
08942142.2%
 
141361.9%
 
1.09890109940< 0.1%
 
1.136< 0.1%
 
1335< 0.1%
 
1.4630< 0.1%
 
1.1524< 0.1%
 
1.03524< 0.1%
 
0.96618357520< 0.1%
 
925.940420< 0.1%
 
2820< 0.1%
 
1.026720< 0.1%
 
917< 0.1%
 
31.5068493215< 0.1%
 
0.75757575814< 0.1%
 
4.61036015612< 0.1%
 
24012< 0.1%
 
24.1405335512< 0.1%
 
1.04812< 0.1%
 
3.38164251211< 0.1%
 
1.5110< 0.1%
 
0.510< 0.1%
 
112510< 0.1%
 
-3.510< 0.1%
 
-0.02458471810< 0.1%
 
Other values (80279)11813355.7%
 
ValueCountFrequency (%) 
-94866.868511< 0.1%
 
-92542.442021< 0.1%
 
-84931.259741< 0.1%
 
-80925.398831< 0.1%
 
-80663.660231< 0.1%
 
-80271.579221< 0.1%
 
-79379.355541< 0.1%
 
-74434.844261< 0.1%
 
-72734.8121< 0.1%
 
-72319.208861< 0.1%
 
ValueCountFrequency (%) 
67809061< 0.1%
 
67647211< 0.1%
 
67507391< 0.1%
 
67384621< 0.1%
 
51040781< 0.1%
 
50279161< 0.1%
 
49515571< 0.1%
 
48749461< 0.1%
 
47982161< 0.1%
 
47218381< 0.1%
 

Graph_Order
Real number (ℝ)

MISSING

Distinct71
Distinct (%)< 0.1%
Missing27027
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean320.7333902
Minimum-1
Maximum70104
Zeros0
Zeros (%)0.0%
Memory size1.6 MiB
2020-12-12T15:22:13.531493image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile1
Q130
median80
Q3130
95-th percentile210
Maximum70104
Range70105
Interquartile range (IQR)100

Descriptive statistics

Standard deviation4027.042602
Coefficient of variation (CV)12.55573235
Kurtosis295.8248985
Mean320.7333902
Median Absolute Deviation (MAD)50
Skewness17.25544704
Sum59363581
Variance16217072.12
MonotocityNot monotonic
2020-12-12T15:22:13.612063image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10193389.1%
 
70187658.8%
 
80174988.2%
 
40100334.7%
 
3096604.6%
 
13096454.5%
 
10093324.4%
 
11093064.4%
 
12090474.3%
 
9089464.2%
 
-169323.3%
 
157082.7%
 
15050362.4%
 
2049032.3%
 
5048042.3%
 
18047732.3%
 
22046892.2%
 
14045882.2%
 
16045252.1%
 
20044662.1%
 
21044512.1%
 
1613950.2%
 
2503660.2%
 
2303660.2%
 
1713640.2%
 
Other values (46)71513.4%
 
(Missing)2702712.7%
 
ValueCountFrequency (%) 
-169323.3%
 
157082.7%
 
10193389.1%
 
2049032.3%
 
3096604.6%
 
40100334.7%
 
5048042.3%
 
70187658.8%
 
80174988.2%
 
9089464.2%
 
ValueCountFrequency (%) 
7010427< 0.1%
 
7010222< 0.1%
 
7010129< 0.1%
 
700996< 0.1%
 
700986< 0.1%
 
700976< 0.1%
 
7007933< 0.1%
 
7007833< 0.1%
 
7007633< 0.1%
 
7006621< 0.1%
 

Interactions

2020-12-12T15:22:02.444453image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:02.566057image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:02.695668image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:02.839293image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:02.982416image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.135547image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.270664image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.396272image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.510370image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.626970image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.743070image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.858670image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:03.979274image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.109886image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.226486image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.368608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.487711image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.608315image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.730920image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.852025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:04.969125image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.091230image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.212335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.331437image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.455043image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.575647image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.692748image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.811350image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:05.930953image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.053058image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.180167image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.300271image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.418873image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.539977image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.660581image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:06.780184image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-12T15:22:13.685126image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-12T15:22:13.776705image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-12T15:22:13.869284image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-12T15:22:13.981381image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-12T15:22:14.132511image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-12T15:22:07.484790image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:08.040769image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:08.905513image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T15:22:09.216781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

country_idcountrycountry_esParent1NameParent1Name_esParent2NameParent2Name_esParent3NameParent3Name_esParent4NameParent4Name_esind_iddescriptiondescription_escodecomm_idCategoryunityearvalueCommoditieCommoditie_esunitusdvalueusdGraph_Order
0JMJAMAICAJAMAICAReference Price (at farm gate)Precio de Referencia (Precio en finca)NaNNaNNaNNaNNaNNaN7.0Reference Price (at farm gate)Precio de Referencia (Precio en finca)RP312JMD/t201389530.900000Poultry MeatCarne de PolloUSD/t888.46775870.0
1SRSURINAMESURINAMLevel of ConsumptionNivel de ConsumoNaNNaNNaNNaNNaNNaN4.0Level of ConsumptionNivel de ConsumoQC42000t20123.130000Beef and VealCarne Vacuna000t3.13000040.0
2SRSURINAMESURINAMProducer NPCCPN del ProductorNaNNaNNaNNaNNaNNaN18.0Producer NPCCPN del ProductorPNPC62ratio20071.000000BananasBananoratio1.000000180.0
3BOBOLIVIABOLIVIAReference Price (at farm gate)Precio de Referencia (Precio en finca)NaNNaNNaNNaNNaNNaN7.0Reference Price (at farm gate)Precio de Referencia (Precio en finca)RP42BOB/t200715295.480000Beef and VealCarne VacunaUSD/t1949.94000070.0
4BOBOLIVIABOLIVIATotal Value of Consumption (at farm gate)Valor Total del Consumo (Precios en finca)NaNNaNNaNNaNNaNNaN102.0Total Value of Consumption (at farm gate)Valor Total del Consumo (Precios en finca)VC01BOBmn200816556.710000Group or not commoditiesNuloUSDmn2178.51000030.0
5SRSURINAMESURINAMProducer Single Commodity TransfersTransferencias al Productor de un Producto IndividualNaNNaNNaNNaNNaNNaN23.0Producer Single Commodity TransfersTransferencias al Productor de un Producto IndividualPSCT243SRDmn200617.941530OrangesNaranjaUSDmn6.45378830.0
6JMJAMAICAJAMAICAProducer Price (at farm gate)Precio al Productor (Precio en finca)NaNNaNNaNNaNNaNNaN2.0Producer Price (at farm gate)Precio al Productor (Precio en finca)PP522JMD/t2008146006.000000Cocoa BeansCacaoUSD/t2002.28000020.0
7NINICARAGUANICARAGUAMarket TransfersTransferencias de MercadoNaNNaNNaNNaNNaNNaN9.0Market TransfersTransferencias de MercadoCT312NIOmn20091254.520000Poultry MeatCarne de PolloUSDmn61.79883090.0
8TTTRINIDAD AND TOBAGOTrinidad y TobagoMarket TransfersTransferencias de MercadoNaNNaNNaNNaNNaNNaN9.0Market TransfersTransferencias de MercadoCT972TTDmn2011-1.700424PapayaPapayaUSDmn-0.26461290.0
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country_idcountrycountry_esParent1NameParent1Name_esParent2NameParent2Name_esParent3NameParent3Name_esParent4NameParent4Name_esind_iddescriptiondescription_escodecomm_idCategoryunityearvalueCommoditieCommoditie_esunitusdvalueusdGraph_Order
212104GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn200861.051232Group or not commoditiesNuloUSDmn7.847202161.0
212105GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn200953.092885Group or not commoditiesNuloUSDmn6.358429161.0
212106GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201054.249815Group or not commoditiesNuloUSDmn6.772761161.0
212107GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn2011120.000000Group or not commoditiesNuloUSDmn15.404365161.0
212108GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201288.030000Group or not commoditiesNuloUSDmn11.254486161.0
212109GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201360.345000Group or not commoditiesNuloUSDmn7.691994161.0
212110GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201471.420000Group or not commoditiesNuloUSDmn9.250804161.0
212111GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201575.390000Group or not commoditiesNuloUSDmn9.867969161.0
212112GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201697.940000Group or not commoditiesNuloUSDmn12.914149161.0
212113GTGUATEMALAGUATEMALAGeneral Services Support Estimate (GSSE)Estimado de Apoyo a Servicios Generales (EASG)H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónNaNNaNNaNNaN167.0H. Agricultural Knowledge and Innovation SystemH. Conocimiento Agropecuario y Sistema de InnovaciónGSSEA01GTQmn201791.380000Group or not commoditiesNuloUSDmn12.463940161.0